Keywords

Strategic Orientation, Organizational Performance, Learning Culture, Jordanian Telecommunication Companies.

Introduction

Nowadays, globalization, severe competition, government regulations, increasing customer demands, and substitute services put huge pressures on firms (Alaali et al., 2021; Alzoubi et al., 221; Nuseir et al., 2021). Accordingly, firms try to have new philosophies that determine the plans, decision-making framework, the nature and scope of their activities, which ensure the growth and sustainability of the firm (Ahmad et al., 2021; Naqvi et al., 2021; Shah et al., 2020). While it is difficult to achieve strategic competitiveness in such complex and turbulent markets, firms use different techniques and styles to achieve the right level of competitive advantage in their pursuit to alleviate such difficulties, which compound and accumulate, while not allowing them to formulate a clear and deep understanding of what affects performance (Al-Dhuhouri et al., 2020; Al Suwaidi et al., 2020; Al Mehrez et al., 2020; Odeh et al., 2021; Obeidat et al., 2021). The core of any strategic orientation is to achieve the right level of performance returns that allows firms to be competitive and to survive over time (Altindag et al., 2011; Abuhashesh et al., 2019). A firm’s strategy influences its structure, investment, activity, relations with the market, and performance. Al-Ansaari et al. (2015) stated that firms can utilize their strategies as a way to create new capabilities and solve problems, while a strategy could provide the framework to help the firm and its managers to deploy required assets, identify new opportunities for providing customers with acceptable products and services, and deliver and sell such products or services in the marketplace with higher profits through strategic orientation.

Strategic orientation is a concept that is intensively used in the research fields of strategic management, entrepreneurship, and marketing (Bing & Zhengping, 2011). The strategic orientation of a firm reflects the strategic directions applied to make the appropriate behaviours for the sustainability and the superior performance of its business (Chahal et al., 2016). Indeed, the firm's competitive landscape is continuously changing, which is forcing them to change, learn, and adapt, in order to survive and grow. To promote better agility to the organization's needs and changing environment, organizations must be designed so that learning is embedded. This requires learning to be at all levels of the organization, such as the individual level, team level, organizational learning, and global level (Bhaskar & Mishra, 2017). Learning culture could be characterized as a culture that creates, integrates, and disseminates knowledge, in addition to modifying itself and transforming its action based on new knowledge, experience, and perceptions to achieve its strategic objectives (Dekoulou & Trivellas, 2015). In order to create superior performance outcomes, Marsick & Watkins (2003) stated that organizations could create a learning culture by creating continuous learning opportunities, promoting inquiry and dialogue, encouraging collaboration and team learning, creating systems to capture and share learning, empowering people towards a collective vision, connecting the organization to its environment, and having strategic leaders to support learning (Kim et al., 2017).

Organizational performance is the end result of activities that include the actual outcomes of the strategic management process (Wheelen et al., 2017). Tomal & Jones (2015) stated that organizational performance is the actual outputs or results of a firm as measured against that firm’s intended outputs. Different studies used many criteria to determine the performance. According to Zehir et al. (2015), performance could be measured by financial and non-financial (operational) indicators. Financial measurements are related to economic indicators, such as profitability and sales growth (e.g., the return on investment, the return on sales, and the return on equity) and non-financial measurements are related to the operational success indicators, such as market share, new product development, quality, satisfaction, and market effectiveness. Nonfinancial performance measurements focus on a firm’s long-term success, such as internal business process efficiency, company image, innovation, customer satisfaction, customer loyalty, employee satisfaction, and employee turnover (Avci et al., 2011; Ammari et al., 2017; Alshurideh et al., 2015; Masa’deh et al., 2013, 2016, 2018; Alameeri et al., 2020; Alkitbi et al., 2020; Alsharari & Alshurideh, 2020; 2020; Kurdi et al., 2020).

This paper is organized as follows: the first section sets the context of the need to study the impact of strategic orientation on organizational performance examining the mediating role of learning culture in Jordanian telecommunication companies. The next section examines the research conceptual framework and hypotheses. The next section indicates the research methodology, and the final section provides the results and research conclusions.

Research Framework and Hypotheses

This research was conducted to study the impact of strategic orientation on organizational performance mediated by learning culture in Jordanian telecommunication companies, where this sector is highly competitive and important.

Operational Definitions

Dependent, independent and mediating variables of the study are operationalized as follows.

Strategic orientation (The Independent Variable)

Strategic orientation indicates the manner in which an organization adapts to its external environment. Market scholars claim that the aforementioned ‘strategic orientation’ is the strategic directions taken by the firm to create behaviours for the business’s continued superior performance (Hunaiti et al., 2009; Moh'd et al., 2013; Tarhini et al., 2015; Wang et al., 2015; Obeidat et al., 2017 a,b; Obeidat et al., 2019). Freitas et al. (2013) argued that the relationship between the strategic orientation of firms and their business activities and performance has been given increasing attention in recent literature, which reflects strategic orientation’s importance. Moreover, Osman (2014) stated that strategic orientation is considered to be closely related to learning and innovation capabilities. It enables information to be generated, disseminated, and, ultimately, transferred into knowledge for the organization. Obeidat (2016) mentioned that there are different strategic orientations, such as technology orientation, innovation orientation, quality orientation, entrepreneurial orientation, market orientation, and productivity orientation, while Mu et al. (2011) mentioned that there are four types of strategic orientations: market orientation, technology orientation, entrepreneurial orientation, and networking orientation. For the purpose of this research, three types of strategic orientation will be looked into further: market orientation, technology orientation, and entrepreneurial orientation.

Market orientation: refers to the extent to which a company’s strategy is sufficiently oriented to its target customers’ needs.

Technology orientation: refers to the extent the company uses sophisticated technologies in the provision of services, and proactively develops new technology ideas.

Entrepreneurial orientation: refers to the degree to which a firm’s business strategy is oriented to acquire, develop, and leverage resources that foster both opportunity- and advantage-seeking behaviours, and response to the industry changes.

Learning culture (The Mediating Variable)

The concept of learning culture has received massive attention in the fields of organizational development, organizational change, strategic management, and human resource development as an inducer of better organizational performance (Alkalha et al., 2012; Pokharel and Choi, 2015; Alshraideh et al., 2017; Al Kurdi et al., 2020; AlMehrzi et al., 2020; Al Naqbi et al., 2020; AlShehhi et al., 2020; Alsuwaidi et al., 2020). In addition, Malik and Garg (2017) stated that an organization’s effort to create learning opportunities for all its members is a definitive example of a learning culture. In order to achieve superior performance outcomes, Marsick & Watkins (2003) suggested that organizations could create a learning culture by using the seven concepts of DLOQ: create continuous learning opportunities, promote inquiry and dialogue, encourage collaboration and team learning, create systems to capture and share learning, empower people towards a collective vision, connect the organization to its environment, and having strategic leaders to support learning (Kim et al., 2017).

Continuous learning: refers to the degree to which employees have opportunities for ongoing learning and learning support.

Promoting inquiry and dialogue: refers to how well organizational culture supports questioning, feedback, experimentation, listening, and inquiring about the views of others.

Collaboration and team learning: refers to what extent the work is designed to use teams to access different modes of thinking and freedom to adapt goals.

Creating systems to capture and share learning: refers to how well the organization creates necessary systems to share learning, and is integrated with work, in addition to measuring the training and sharing of lessons.

Empowering people towards a collective vision: Refers to the extent that people are involved in setting and implementing a shared vision.

Connecting the organization to its environment: Refers to how well the organization is linked to its communities, understands the overall environment, and uses information to adjust work practices.

Strategic leadership: refers to how well the leadership uses learning strategically for business results, leader’s models, championing, and supporting learning.

Firm Performance (The Dependent Variable)

Organizational performance is the end result of activities that include the actual outcomes of the strategic management process (Wheelen et al., 2017). Tomal & Jones (2015) stated that organizational performance is the actual outputs or results of a firm as measured against that firm’s intended outputs. Different studies used many criteria to determine the performance. According to Zehir et al. (2015), performance could be measured by financial and non-financial (operational) indicators. Therefore, non-financial (operational) indicators used to measure the firm performance in this research.

Non-financial performance (Operational Performance): refers to the telecommunication company's ability to focus on a firm’s long-term success, such as internal business process efficiency, company image, innovation, customer satisfaction, customer loyalty, and employee satisfaction.

Measurement of Variables

Primary data was collected from the questionnaire, which was constructed based on the research model developed from the related literature, as follows: strategic orientation (Mu et al., 2011; Al-Ansaari et al., 2015), learning culture (Song et al., 2009), and organizational performance (Tseng & Lee, 2014). The questionnaire used a Likert-type scale with five scale categories: (1 strongly disagree, 2 Disagree, 3 Neutral, 4 Agree, 5 strongly Agree). The questions were divided into four sections representing: demographic variables, strategic orientation, learning culture, and organizational performance.

Strategic orientation (The Independent Variable)

Table 1 Strategic Orientation Measurement
Strategic orientation
Dimensions	Items
Market Orientation	Our business objectives are driven primarily by customer satisfaction
	We constantly monitor our level of commitment and orientation to serve customers’ needs
	Our strategy for competitive advantage is based on our understanding of customers’ needs
	Our business strategies are driven by our beliefs about how we can create greater value for customers
	We measure customer satisfaction systematically and frequently
	We give close attention to after-sales service
Technology Orientation	Our company technical innovation based on research results is readily accepted
	The company Management actively seeks innovative ideas
	Our company allocates resources for investments in latest technologies and future forecasted technological changes
	In our company People are encouraged to have new ideas for new services
Entrepreneurial Orientation	We have built capacity to react to market changes
	We protect our advantages from industry changes
	We prepare for radical industry changes
	We believed that wide-ranging acts were necessary to achieve objectives
	We initiated actions to which other organizations respond

Learning culture (The Mediating Variable)

Table 2 Learning Culture Measurement
Learning culture
Dimensions	Items
Continuous Learning	We help each other to learn
	We take time to support learning
	We being rewarded for learning
Promoting Inquiry and Dialogue	We provide open feedback
	We ask what others think
	We spend time building trust
Collaboration and Team Learning	We have freedom to adapt goals
	We revise thinking with information
	We act on our recommendations
Creating systems to capture and share learning	Our company creates measurement system
	Our company makes the lessons learned available
	Our company measures the results of training
Empowering people toward a collective vision	Our company recognize for taking initiative
	Our company give people control over resource
	Our company supports calculated risk-taking
Connecting the organization to its environment	Our company encourage global perspectives
	Our company work with outside/resources
	Our company encourage diverse perspectives
Strategic Leadership	Our company provides mentoring/coaching
	Our company provides opportunities to learn
	Our company ensures the consistent actions

Organizational Performance (The Dependent Variable)

Table 3 Non – Financial Performance Measurement
Non – financial performance (Operational performance)
Dimensions	Items
Our company is able to grasp the right timing for launching new services
Our company is equipped with the ability to develop high-quality new services
The launch speed of new services is faster than other companies in the same industry
The degree of automation operation is much higher than other companies in the same industry
Our company is able to adjust or change our management process based on the market competition
Our company is able to retain outstanding staff
Our company is active in nurturing staff’s leadership
Our company puts high value on our staff’s satisfaction on our corporate measures
Our company has an excellent staff welfare policy
Our company possesses comprehensive plans for our Future
Our company vigorously invests in the development of new markets

The research model is developed by the researcher based on the related literature as follows: Strategic orientation based on (Mu et al., 2011; Al-Ansaari et al., 2015), learning culture based on (Song et al., 2009), and organizational performance based on (Tseng and Lee, 2014).

Research Hypotheses

First Main Hypothesis

H0₁: There is no statistically significant impact of strategic orientation on organizational performance at a significant level of α ≤ 0.05.

Sub-Hypotheses of the First Main Hypothesis:

H0_1.1: There is no statistically significant impact of market orientation on organizational performance at a significant level of α ≤ 0.05.

H0_1.2: There is no statistically significant impact of technology orientation on organizational performance at a significant level of α ≤ 0.05.

H0_1.3: There is no statistically significant impact of entrepreneurial orientation on organizational performance at a significant level of α ≤ 0.05.

Second Main Hypothesis

H0₂: There is no statistically significant impact of strategic orientation on learning culture at a significant level of α ≤ 0.05.

Sub-Hypotheses of the Second Main Hypothesis:

H0_2.1: There is no statistically significant impact of market orientation on learning culture at a significant level of α ≤ 0.05.

H0_2.2: There is no statistically significant impact of technology orientation on learning culture at a significant level of α ≤ 0.05.

H0_2.3: There is no statistically significant impact of entrepreneurial orientation on learning culture at a significant level of α ≤ 0.05.

Third Main Hypothesis

H0₃: There is no statistically significant impact of learning culture on organizational performance at a significant level of α ≤ 0.05.

Sub-Hypotheses of the Third Main Hypothesis:

H0_3.1: There is no statistically significant impact of continuous learning on organizational performance at a significant level of α ≤ 0.05.

H0_3.2: There is no statistically significant impact of promoting inquiry and dialogue on organizational performance at a significant level of α ≤ 0.05.

H0_3.3: There is no statistically significant impact of collaboration and team learning on organizational performance at a significant level of α ≤ 0.05.

H0_3.4: There is no statistically significant impact of creating systems to capture and share learning on organizational performance at a significant level of α ≤ 0.05.

H0_3.5: There is no statistically significant impact of empowering people toward a collective vision on organizational performance at a significant level of α ≤ 0.05.

H0_3.6: There is no statistically significant impact of connecting the organization to its environment on organizational performance at a significant level of α ≤ 0.05.

H0_3.7: There is no statistically significant impact of strategic leadership on organizational performance at a significant level of α ≤ 0.05.

Fourth Main Hypothesis

H0₄: There is no statistically significant mediating role of learning culture on the impact of strategic orientation on organizational performance at a significant level of α ≤ 0.05.

Research Population, Sample, and Data Collection

The population of this study is the three telecommunication companies in Amman (Zain, Orange, and Umniah) consisted of 2,211 employees of all managerial and non-managerial positions.

Table 4 Number Of Employees at Each Company
Company name	Zain	Umniah	Orange
Number of employees	1012	654	545

The population of this study consisted of 2,211 employees. According to Sekaran and Bougie (2013), the sample size for this population must be 318 employees. To arrive at this size, a paper questionnaire was distributed to employees in various branches of the three companies, in addition to an electronic questionnaire that was send by email and to LinkedIn accounts.

Validity and Reliability

Validity tests how well the instrument measures the concepts it is supposed to measure, and if it measures the right concept (Sekaran and Bougie, 2013). This measure of goodness is seen as the most important criterion of research (Bryman and Bell, 20015).

Content Validity

Content validity was employed in this research to check the validity of the research instrument. Therefore, to ensure that the instrument developed for this research is valid, a pilot study was conducted using the procedure suggested by Peat et al. (2002). The questionnaire was administered to participants in exactly the same way as it would be in the main study. The participants were asked to complete the questionnaire and provide feedback to identify ambiguities and difficult questions. According to their feedback, any ambiguous questions were redrafted.

Construct Validity

Construct validity refers to “how well the results obtained from the use of the measure fit the theories around which the test is designed” (Sekaran & Bougie, 2013). It is regarded as the heart of any study, where a measure has been used as an index of a variable that cannot be directly observed. One way to examine construct validity is through the use of factor analysis. The results revealed that all the factors had Eigen values greater than (1) and all the items had loadings greater than (0.30). Fulfilling the assumptions mentioned previously, a three-factor model of strategic orientation emerged explaining (58.978%) of the total variance which is within the (50-60%) range suggested by Hair et al. (2010) for humanities studies. The pattern matrix which displays the rotated factor loadings is used to interpret the dimensions (Williams et al., 2010). The factors extracted coincide with the dimensions used in this study as can be seen in table (5). Items that load on the first dimension suggest that it represents group 1 and includes 9 items used to measure it, items that load on the second dimension suggest that it represents group 2 and includes 6 items used to measure it.

Regarding learning culture, all of the 21 items were loaded without any deletion or addition. A seven-factor model emerged explaining (66.698%) of the total variance which is within the (50-60%) range suggested by Hair et al. (2010) for humanities studies. The factors extracted coincide with the dimensions used in this study as can be seen in table (6). Items that load on the first dimension suggest that it represents group 1 and includes 18 items used to measure it, items that load on the second dimension suggest that it represents group 2 and includes 3 items used to measure it. All of the items of organization performance were loaded on to two factors indicating that none of the items were deleted. A two-factor model emerged explaining (65.162%) of the total variance. The factors extracted coincide with the dimensions used in this study as can be seen in table (7). Items that load on the first dimension suggest that it represents group 1 and includes 8 items used to measure it. Items that load on the second dimension suggest that it represents group 2 and includes 4 items used to measure it. Hence, based on the results obtained from EFA it can be concluded that construct validity is confirmed.

Strategic Orientation (The Independent Variable)

Table 5 Pattern Matrix for Strategic Orientation
Strategic Orientation	Component
	1	2
Our company allocates resources for investments in latest technologies and future forecasted technological changes	.818
We prepare for radical industry changes	.770
In our company People are encouraged to have new ideas for new services	.737
Our company technical innovation based on research results is readily accepted	.735
We believed that wide-ranging acts were necessary to achieve objectives	.675
The company Management actively seeks innovative ideas	.666
We protect our advantages from industry changes	.656
We initiated actions to which other organizations respond	.633
We have built capacity to react to market changes	.612
Our business objectives are driven primarily by customer satisfaction		1.010
We constantly monitor our level of commitment and orientation to serve customers’ needs		.924
Our strategy for competitive advantage is based on our understanding of customers’ needs		.813
Our business strategies are driven by our beliefs about how we can create greater value for customers		.745
We measure customer satisfaction systematically and frequently		.579
We give close attention to after-sales service		.528
Extraction Method: Principal Component Analysis. Rotation Method: Promax with Kaiser Normalization.

Learning Culture (The Mediating Variable)

Table 6 Pattern Matrix for Learning Culture
Learning Culture	Component
	1	2
We spend time building trust	.939
We provide open feedback	.930
We take time to support learning	.917
We being rewarded for learning	.915
We ask what others think	.907
We have freedom to adapt goals	.863
We help each other to learn	.817
We act on our recommendations	.773
Our company creates measurement system	.762
Our company give people control over resource	.713
Our company makes the lessons learned available	.643
Our company recognize for taking initiative	.606
Our company measures the results of training	.603
We revise thinking with information	.584
Our company ensures the consistent actions	.510
Our company provides opportunities to learn	.489
Our company provides mentoring/coaching	.458
Our company supports calculated risk-taking	.443
Our company work with outside/resources		1.028
Our company encourage global perspectives		.967
Our company encourage diverse perspectives		.744
Extraction Method: Principal Component Analysis. Rotation Method: Promax with Kaiser Normalization.

Organization Performance (The dependent Variable)

Table 7 Pattern Matrix for Organization Performance
Organization Performance	Component
	1	2
Our company is able to grasp the right timing for launching new services	.929
Our company possesses comprehensive plans for our Future	.822
Our company is equipped with the ability to develop high-quality new services	.816
Our company vigorously invests in the development of new markets	.759
The launch speed of new services is faster than other companies in the same industry	.711
Our company vigorously invests in the development of new technology	.657
The degree of automation operation is much higher than other companies in the same industry	.605
Our company is able to adjust or change our management process based on the market competition	.310
Our company puts high value on our staff’s satisfaction on our corporate measures		.917
Our company is active in nurturing staff’s leadership		.908
Our company has an excellent staff welfare policy		.902
Our company is able to retain outstanding staff		.843
Extraction Method: Principal Component Analysis. Rotation Method: Promax with Kaiser Normalization.

Reliability

To ensure that the instrument used in this study will be as reliable as possible, the researcher conducted a pilot study. Pilot studies are used in social science research in two ways: as a small-scale version in preparation of the major research (feasibility studies), in addition to pre-testing of a particular research instrument (Van and Hundley, 2002). Reliability is established using a pilot study by collecting data from 20-30 subjects not included in the sample, the data collected from pilot study are then analyzed using SPSS to determine the Cronbach’s alpha coefficient for each variable (Radhakrishna, 2007). The researcher administered questionnaires to 20 employees from the three companies. The data were collected and analyzed and the results obtained attested to the reliability of the instrument since all the measures had Cronbach’s alpha coefficients of 0.60 and above (see table 8) as suggested by Hair et al. (2010).

Table 8 Cronbach’s Alpha of Study Instrument Based on Pilot Study
Variable	Number of items	Cronbach’s Alpha (α)
Strategic Orientation	15	.842
Learning Culture	21	.870
Organization Performance	12	.936

The pilot study can help improve the reliability of the instrument by indicating which items can be deleted to raise the value of alpha (Radhakrishna, 2007). Once the final version of the questionnaire was distributed to the sample and collected, the Cronbach’s alpha values were calculated to determine the internal reliability for the study instrument. The results obtained in table (9) showed that the reliability of the study variables is much higher than the accepted level, where Hair et al. (2010) suggested that the minimum accepted level for (α) is 0.60. This indicates that the study instrument has a high degree of reliability.

Table 9 Reliability Statistics
Variable	Cronbach’s Alpha	No. of items
Strategic Orientation	0.842	15
Market Orientation	.885	6
Technology Orientation	.920	4
Entrepreneurial orientation	.807	5
Learning Culture	0.870	21
Continuous Learning	0.837	3
Promoting Inquiry and Dialogue	0.824	3
Collaboration and Team Learning	0.819	3
Creating systems to capture and share learning	0.816	3
Empowering people toward a collective vision	0.891	3
Connecting the organization to its environment	0.848	3
Strategic Leadership	0.873	3
Organization Performance	0.936	12
Non-financial performance (operational performance)	0.936	12

Research Results

Demographic Characteristics of Respondents

The respondents of this study were asked to provide information regarding their gender, age, educational level, experience, and managerial level. Table 10 presents the demographic profile of the respondents with the frequency and the percentage.

Table 10 The Attributes of Respondents
	Frequency	Percent
Gender
Male	180	56.1%
Female	141	43.9%
Total	321
Age
From 20-Less than 25 years	67		20.9%
From 25-Less than 30 years	95		29.6%
From 30-Less than 35 years	82		25.5%
35 – less than 40 years	49		15.3%
40 years and above	28		8.7%
Total	321
Educational Level
Diploma	32		10.0%
Bachelor Degree	247		76.9%
Master’s Degree	40		12.5%
Doctorate Degree	2		.6%
Total	321
Experience
Less than 5 years	126		39.3%
5 – less than 10 years	97		30.2%
10 – less than 15 years	70		21.8%
15 –less than 20 years	25		7.8%
20 years and more	3		.9%
Total	321
Managerial level
Senior management level (CEO, GM)	8		2.5%
Middle management level (division manager, functional manager)	67		20.9%
Lower management level (head of department)	81		25.2%
Non managerial employee	165		51.4%
Total	321

As can be seen in table 10, the demographic profile of the respondents shows that (56.1%) of them were male and (43.9%) female. Regarding the age of the respondents, (20.9%) of them belong to age group of 20-Less than 25 years, (29.6%) belong to age group of 25-Less than 30 years, (25.5%) belong to age group of 30-Less than 35 years, (15.3%) belong to age group of 35 – less than 40 years and (8.7%) belong to age group of 40 years and above. In terms of educational level of the respondents, it can be seen that the majority of them hold a bachelor degree with a percentage of (76.9%), followed by (12.5%) holding master's degree, (10.0%) holding diploma and only (0.6%) holding doctorate degree. When considering the experience of the respondents, (39.3%) have less than 5 years of experience, (30.2%) have 5 – less than 10 years of experience, (21.8%) have 10 – less than 15 years of experience, (7.8%) have 15 –less than 20 years of experience and only (0.9%) have 20 years and more years of experience. Regarding the managerial level of the respondents, most of them (51.4%) are non-managerial employee, while (25.2%) are lower management level (head of department), (20.9%) are middle management level (division manager, functional manager) and only (2.5%) are senior management level (CEO, GM).

Hypotheses Testing

First Main Hypothesis

H0₁: There is no statistically significant impact of strategic orientation on organizational performance at a significant level of α ≤ 0.05.

H0_1.1: There is no statistically significant impact of market orientation on organizational performance at a significant level of α ≤ 0.05.

H0_1.2: There is no statistically significant impact of technology orientation on organizational performance at a significant level of α ≤ 0.05.

H0_1.3: There is no statistically significant impact of entrepreneurial orientation on organizational performance at a significant level of α ≤ 0.05.

Table 11 Multiple Regression of the First Hypotheses
	R	R2	Adjusted R2	F-value	Sig	Standardized Beta	t-value	Sig
Market Orientation	0.763	0.583	0.574	68.377	0.000	0.246	3.367	0.001
Technology Orientation						0.461	5.944	0.000
Entrepreneurial orientation						0.166	2.500	0.014

The correlation coefficient R=0.763 indicates that there is a positive correlation between strategic orientation and organization performance as mentioned above. This proves that the independent variables and dependent variable change in the same direction. R square, coefficient of determination, provides information regarding the goodness of fit of the regression model (Sekaran & Bougie, 2013). In other words, it represents the percentage of variance in the dependent variable that is explained by the variation in the independent variable (Sekaran & Bougie, 2013). The value of R²=0.583 indicates the number of variations in organization performance that is accounted by the fitted model and has been explained by strategic orientation. The adjusted R² indicates the generalize ability of the model. It allows generalizing the results taken from the respondents to the whole population. It is noticed that the value of the adjusted R² = 0.574 is close to the value of R² = 0.583. If the adjusted R² is excluded from R² the value will be (0.583-0.574=0.009). This amount of reduction means that if the whole population participates in the study and the model has been fitted then, there will be 0.9% reduction in the variance of the outcome.

The next step is the analysis of variance (ANOVA) that allows us to statistically test the main null hypothesis. The results of the ANOVA table show that the F-ratio= 68.377 which is significant at level p<0.05 (sig.< 0.001), this result indicates that there is less than 5% chance that an F-ratio of this value would occur by chance alone. Since the p-value is smaller than the level of significance (0.05), the null hypothesis is rejected at p< 0.05 significance level. Hence, there is a statically significant impact of strategic orientation on organizational performance. Results from the coefficients table, the t and sig. (which is known as p-value) values. A large absolute t-value and small p-value suggests that the predictor variable does contribute to the criterion variable. The results show that all the dimensions of strategic orientation are significant contributors to organization performance (p-value<0.05). Furthermore, the standardized beta coefficient is a measure of the contribution of the predictor variable to the criterion variable. A large value indicates that a unit change in this predictor variable has a large effect on the criterion variable. In this study use of technology orientation has the most contribution to organization performance with a β of 0.461 which indicates that it is a strong predictor of organization performance. Market orientation and entrepreneurial orientation follow with β values of 0.246 and 0.166, respectively. Based on the results obtained from the multiple regressions the following decisions can be made regarding the sub hypotheses of the first main hypothesis.

Table 12 The Results of Testing the First Null Hypotheses
Sub Hypotheses	Result
H01.1: There is no statistically significant impact of market orientation on organizational performance at a significant level of α ≤ 0.05.	Rejected
H01.2: There is no statistically significant impact of technology orientation on organizational performance at a significant level of α ≤ 0.05.	Rejected
H01.3: There is no statistically significant impact of entrepreneurial orientation on organizational performance at a significant level of α ≤ 0.05.	Rejected

The results of testing the sub hypotheses for the first main hypothesis showed rejection to the null hypothesis of H_01.1, H_01.2, H_01.3 and acceptance of the alternative hypothesis that there is a statistically significant impact of market orientation, technology orientation, and entrepreneurial orientation, on organizational performance at a significant level of α ≤ 0.05. Indeed, the results from testing the first main hypothesis revealed that strategic orientation and organization performance are significantly related. Thus, it can be concluded that there is a tendency for high levels of organization performance in telecommunication companies to be associated with a high level of strategic orientation. This finding confirms the findings obtained in other studies, where strategic orientation has a positive relationship with organizational performance in the workplace (Altindag et al., 2011; Thoumrungroje & Racela, 2013; Sarker & Palit, 2015; Al-Ansaari et al., 2015; Chahal et al., 2016; Nasir et al., 2017). The premise behind this finding may relate to the fact that, nowadays, telecommunication companies in Jordan face increasing customer demands due to the increase in the population, severe competition, and intensive and rapid growth in technology; all of these conditions oblige these companies to adapt to the external environment, and take strategic directions that create the proper behaviours for a continuously superior performance. In addition, they must have a strategic orientation that portrays the organization’s marketing, operational, and entrepreneurial posture, which refers to how an organization achieves its goals by becoming proactive in its risk taking, investments in innovation, and development of future-oriented foresight.

Second Main Hypothesis

H0₂: There is no statistically significant impact of strategic orientation on learning culture at a significant level of α ≤ 0.05.

H0_2.1: There is no statistically significant impact of market orientation on learning culture at a significant level of α ≤ 0.05.

H0_2.2: There is no statistically significant impact of technology orientation on learning culture at a significant level of α ≤ 0.05.

H0_2.3: There is no statistically significant impact of entrepreneurial orientation on learning culture at a significant level of α ≤ 0.05.

Table 13 Multiple Regression of the Second Hypotheses
	R	R2	Adjusted R2	F-value	Sig	Standardized Beta	t-value	Sig
Market Orientation	0.805	0.649	0.642	90.531	0.000	0.190	2.841	0.005
Technology Orientation						0.603	8.471	0.000
Entrepreneurial Orientation						0.097	1.590	0.114

The correlation coefficient R=0.805 indicates that there is a positive correlation between strategic orientation and learning culture as mentioned previously. This positive relationship suggests that the independent variable and dependent variable move in the same direction. The value of R²=0.649 indicates the number of variations in learning culture that is accounted by the fitted model and has been explained by strategic orientation. The adjusted R² indicates the generalize ability of the model. It allows generalizing the results taken from the respondents to the whole population. It is noticed that the value of the adjusted R²=0.642is very close to the value of R²=0.0.649. If the adjusted R² is excluded from R² the value will be (0.649-0.642=0.007). This amount of reduction means that if the whole population participates in the study and the model has been fitted then, there will be 0.7% less variance in the outcome. The analysis of variance (ANOVA) allows us to statistically test the main null hypothesis. The results show that the F-ratio=90.531 and p-value< 0.001, this result indicates that there is less than 5% chance that an F-ratio of this value would occur solely by chance. Since the p-value is smaller than the level of significance (0.05), the null hypothesis is rejected at p<0.05 significance level. Hence, there is a statically significant impact of strategic orientation on learning culture.

The results obtained from the coefficients table indicate that technology orientation contributes the most to learning culture given that β=0.603. In addition, market orientation was considered significant predictors of learning culture given that it had significant betas of 0.190. Entrepreneurial orientation is not considered a significant predictor of learning culture since its p-value = 0.114 is greater than 0.05. Based on the results of conducting the multiple regression analysis for the second main hypothesis the following decisions can be made regarding the sub hypotheses of the second main hypothesis.

Table 14 The Results of Testing the Second Null Hypotheses
Sub Hypotheses	Result
H02.1: There is no statistically significant impact of market orientation on learning culture at a significant level of α ≤ 0.05.	Rejected
H02.2: There is no statistically significant impact of technology orientation on learning culture at a significant level of α ≤ 0.05.	Rejected
H02.3: There is no statistically significant impact of entrepreneurial orientation on learning culture at a significant level of α ≤ 0.05.	Accepted

The results of testing the sub hypotheses for the second main hypothesis showed a rejection to the null hypothesis of H_02.1, H_02.2 and acceptance of the alternative hypothesis that there is a statistically significant impact of market orientation and technology orientation on learning culture at a significant level of α ≤ 0.05.The results showed acceptance of the null hypothesis of H_02.3 that there is no statistically significant impact of entrepreneurial orientation on learning culture at a significant level of α ≤ 0.05.The premise behind this result may relate to the fact that telecommunication companies in Jordan should increase their coping ability through building a learning culture and entrepreneurial innovativeness. In addition, it should ensure that staff possesses required line competencies. Moreover, these companies should continually put into effect experiences learnt from past challenges to be effectively proactive and responsive.

Indeed, the results of testing the second main hypothesis revealed that strategic orientation and learning culture are significantly related, and there is a positive correlation between strategic orientation and learning culture. This finding confirms the findings obtained in other studies, where strategic orientation has a positive relationship with learning culture in the workplace (Slater and Narver, 1995; Santos et al., 2005; Onyema, 2014; Real et al., 2014; Stephen et al., 2017; Abu Zayyad et al., 2020). The premise behind this finding may relate to the fact that telecommunication companies in Jordan are aware that strategic orientation is considered to be closely related to learning capabilities and knowledge sharing. On the other hand, it enables information to be generated, disseminated, and ultimately transferred into knowledge for the organization. Moreover, strategic orientation is used as a way of improving the organization’s competitive performance, as well as a way of motivating the knowledge-based competitive performance of the organization, which directs organizational managers’ attention towards using the strategic orientation to build the learning culture, and perceiving that it is vital to the immediate and future directions of the organization.

Third Main Hypothesis

H0₃: There is no statistically significant impact of learning culture on organizational performance at a significant level of α ≤ 0.05.

H0_3.1: There is no statistically significant impact of continuous learning on organizational performance at a significant level of α ≤ 0.05.

H0_3.2: There is no statistically significant impact of promoting inquiry and dialogue on organizational performance at a significant level of α ≤ 0.05.

H0_3.3: There is no statistically significant impact of collaboration and team learning on organizational performance at a significant level of α ≤ 0.05.

H0_3.4: There is no statistically significant impact of creating systems to capture and share learning on organizational performance at a significant level of α ≤ 0.05.

H0_3.5: There is no statistically significant impact of empowering people toward a collective vision on organizational performance at a significant level of α ≤ 0.05.

H0_3.6: There is no statistically significant impact of connecting the organization to its environment on organizational performance at a significant level of α ≤ 0.05.

H0_3.7: There is no statistically significant impact of strategic leadership on organizational performance at a significant level of α ≤ 0.05.

Table 15 Multiple Regression of the Third Hypotheses
	R	R2	Adjusted R2	F-value	Sig	Standardized Beta	t-value	Sig
Continuous Learning	0.804	0.647	0.639	81.908	.000	0.062	1.072	0.285
Promoting Inquiry and Dialogue						0.185	2.647	0.009
Collaboration and Team Learning						0.189	2.611	0.009
Creating systems to capture and share learning						0.050	.725	0.469
Empowering people toward a collective vision						0.145	2.371	0.018
Connecting the organization to its environment						0.168	3.692	0.000
Strategic Leadership						0.242	3.973	0.000

The correlation coefficient R = 0.804 which indicates that the relationship between learning culture and organizational performance is positive and that both variables change in the same direction. The coefficient of variation R² shows that 64.7% of the variation in the dependent variable (organization performance) is explained by the independent variable (learning culture). The adjusted R² indicates the generalize ability of the model. It allows generalizing the results taken from the respondents to the whole population. It is noticed that the value of the adjusted R²=0.647is close to the value of R²=0.639. If the adjusted R² is excluded from R² the value will be (0.647-0.639=0.008). This amount of reduction means that if the whole population participates in the study and the model has been fitted then, there will be 0.8% less variance in the outcome. The analysis of variance (ANOVA) allows us to statistically test the main null hypothesis. The above table shows the results of the ANOVA test, where the F-ratio= 81.908 and the p-value= 0.000, this result indicates that there is less than 5% chance that an F-ratio of this value would occur solely by chance. Since the p-value (< 0.001) is smaller than the significance level (0.05), the null hypothesis is rejected and the alternative hypothesis is accepted indicating that there is an impact of learning culture on organizational performance.

The results in the coefficients table revealed that promoting inquiry and dialogue, collaboration and team learning, empowering people toward a collective vision, connecting the organization to its environment, and strategic leadership significantly predicted organization performance given that their significant betas were 0.185, 0.189, 0.145, 0.168 and 0.242, respectively. The other two dimensions, continuous learning and creating systems to capture and share learning were not significant since their p-values were greater than 0.05. Therefore, the following decisions can be made regarding the sub hypotheses of the third main hypothesis.

Table 16 The Results of Testing the Third Null Hypotheses
Sub Hypotheses	Result
H03.1: There is no statistically significant impact of continuous learning on organizational performance at a significant level of α ≤ 0.05.	Accepted
H03.2: There is no statistically significant impact of promoting inquiry and dialogue on organizational performance at a significant level of α ≤ 0.05.	Rejected
H03.3: There is no statistically significant impact of collaboration and team learning on organizational performance at a significant level of α ≤ 0.05.	Rejected
H03.4: There is no statistically significant impact of creating systems to capture and share learning on organizational performance at a significant level of α ≤ 0.05.	Accepted
H03.5: There is no statistically significant impact of empowering people toward a collective vision on organizational performance at a significant level of α ≤ 0.05.	Rejected
H03.6: There is no statistically significant impact of connecting the organization to its environment on organizational performance at a significant level of α ≤ 0.05.	Rejected
H03.7: There is no statistically significant impact of strategic leadership on organizational performance at a significant level of α ≤ 0.05.	Rejected

The results of testing the sub hypotheses for the third main hypothesis showed rejection of the null hypothesis of H_03.2, H_03.3, H_03.5, H_03.6, H_03.7and acceptance of the alternative hypothesis that there is a statistically significant impact of promoting inquiry and dialogue, collaboration and team learning, empowering people towards a collective vision, connecting the organization to its environment, and strategic leadership on organizational performance at a significant level of α ≤ 0.05.While, the results showed acceptance of the null hypothesis of H_03.1, H_03.4that there is no statistically significant impact of continued learning and creating systems to capture, and sharing learning on organizational performance at a significant level of α ≤ 0.05.The premise behind these results may relate to the fact that telecommunication companies in Jordan should draw the attention of managers to the need to pay attention to directing employees to helping each other to learn, taking time to support learning, and rewarding employees for learning. In addition, these companies must create measurement systems for learning, make the lessons learned available for all the employees, and measure the results of employee training to build a vital learning culture that improves organizational performance.

Indeed, the results of testing the third main hypothesis revealed that the relationship between learning culture and organizational performance is positive, and that both variables change in the same direction. This finding confirms the findings obtained in other studies, where learning culture has a positive relationship with organizational performance in the workplace (Marsick and Watkins, 2003; Alshurideh et al., 2012; Bai and Fallah, 2012; Yu and Chen, 2012; Pokharel and Choi, 2015; Lim et al., 2016; Cooper et al., 2016; Wahda, 2017; Bhaskar and Mishra, 2017; Malik and Garg, 2017; Kim et al., 2017; Alshurideh et al., 2021). The premise behind this finding may relate to the fact that telecommunication companies in Jordan are aware of the importance of building a learning culture that is oriented towards the promotion and facilitation of employees’ learning, knowledge sharing, and dissemination, in order to contribute to organizational development and performance. Moreover, these companies must have a learning culture, be skilled at acquiring, creating, and transferring knowledge, in addition to modifying behaviour to apply new knowledge and insights, thereby improving performance and competitiveness.

Fourth Main Hypothesis

H0₄: There is no statistically significant mediating role of learning culture on the impact of strategic orientation on organizational performance at a significant level of α ≤ 0.05.

Mediation is a hypothesized causal chain, in which one variable affects a second variable that, in turn, affects a third variable. The intervening variable, M, is the mediator. It mediates the relationship between a predictor, X, and an outcome (Biesanz et al., 2010). Graphically, mediation can be depicted in the following way (Sekaran & Bougie, 2013):

Paths (a) and (b) are called direct effects, the meditational effect, in which X leads to Y through M, is called the indirect effect. The indirect effect represents the portion of the relationship between X and Y that is mediated by M. To test for mediation, Baron and Kenny (1986) proposed a four-step approach, in which several regression analyses are conducted, and the significance of the coefficients is examined at each step. Table (17) presents a detailed explanation of the approach proposed by Baron and Kenny (1986).

Steps 1-3 establish whether zero-order relationships among the variables exist. If one or more of these relationships are non-significant, researchers usually conclude that mediation is not possible or likely, however this may not always be true (MacKinnon et al., 2007). Assuming there are significant relationships from Steps 1 through 3, one proceeds to Step 4. In the Step 4 model, some form of mediation is supported if the effect of M (path b) remains significant after controlling for X. If X is no longer significant when M is controlled, the finding supports full mediation. If X is still significant (i.e., both X and M both significantly predict Y), the finding supports partial mediation. To test this hypothesis a combination of simple and multiple regression analyses were conducted as proposed by Baron & Kenny (1986). The results of the regression tests can be seen in table 18. It is worth noting that the Baron & Kenny (1986) model of mediation focuses on the unstandardized regression coefficients, therefore, the coefficients mentioned in the below table represent the unstandardized betas.

Table 18 Regression Analysis for Mediation of Strategic Orientation on Organization Performance Through Learning Culture
Step 4 organization Performance	Step 3 organization Performance	Step 2 Learning culture	Step 1 organization Performance	Variables
0.711**	1.127**	0.578**	1.022**	(Constant)
0.317**		0.803**	0.748**	Strategic orientation
0.537**	0.761**			Learning Culture
0.820	0.794	0.753	0.732	R
0.673	0.631	0.566	0.536	R²
0.671	0.630	0.565	0.535	Adj. R²
326.708**	545.360**	416.854**	368.897**	F-value
** p≤ 0.05.

To determine whether learning culture acts as a mediator in the relationship between strategic orientation and organization performance, the following rule should be followed: some form of mediation is supported if the effect of the expected mediator remains significant after controlling for the independent variable. If the independent variable is no longer significant when the expected mediator is controlled, the finding supports full mediation. If the independent variable is still significant (i.e., both the independent variable and the expected mediator significantly predict the dependent variable), the finding supports partial mediation (Baron and Kenny, 1986). Based on this rule, partial mediation exists, since strategic orientation and learning culture, both significantly predict organization performance (p-values= 0.000). Furthermore, the strength of the independent variable in predicting the dependent should be reduced in the presence of the mediator variable in order to support partial mediation. In this case, the unstandardized beta for strategic orientation was reduced from 0.748 to 0.317, which supports the condition for partial mediation. According to Baron and Kenny (1986), having a partial mediation model is more realistic in most social science research because a single mediator cannot be expected to completely explain the relationship between the independent variable and the dependent variable.

Although Baron and Kenny (1986) provide an appealing approach to follow in order to determine the presence or absence of a mediation effect, it is considered necessary to conduct a formal significance test of the indirect effect if the Baron and Kenny criteria have been met (Preacher and Hayes, 2004). This is important for two reasons. First, there are shortcomings related to the Baron and Kenny method. According to Holmbeck (2002) it is possible to observe a change from a significant X→ Y path to a non-significant X →Y when adding a mediator to the model with a very small change in the absolute size of the coefficient. This result my lead a researcher to erroneously conclude that a mediation effect is present (Type I error). Conversely, it is possible to observe a large change in the X →Y path when adding a mediator to the model without observing a change in statistical significance (Type II error). This situation is likely to occur when large samples are employed as those are the conditions under which even small regression weights may remain statistically significant. Second, testing the hypothesis of no difference between the total effect (path c) and the direct effect (path c’) more directly addresses the mediation hypothesis than does the series of regression analyses recommended by Baron and Kenny (1986). In the case of simple mediation, the indirect effect of X on Y through M is measured as the result of the X-M and M-Y path (ab), which is equivalent to (c–c’) in most cases. Thus, a significance test associated with (ab) should address mediation more directly than a series of separate significance tests that do not directly involve (ab) (Preacher and Hayes, 2004).

There are more statistically rigorous methods by which mediation hypotheses may be tested (Preacher and Hayes, 2004). Baron and Kenny (1986) describe a procedure developed by Sobel (1982) that assesses more directly the indirect effect of mediation. According to MacKinnon et al. (2007) the Sobel test is considered a superior test in terms of power and intuitive appeal. The Sobel test is performed by comparing the strength of the indirect effect of X on Y to the point null hypothesis that it equals zero. The indirect effect of X on Y in this situation is defined as the product of the X→ M path (a) and the M-Y path (b), or (ab). In most situations, ab=(c - c’), where c is the simple (i.e., total) effect of X on Y, not controlling for M, and c’ is the X-Y path coefficient after the addition of M to the model. Standard errors of a and b are represented, by s_a and s_b, respectively. The standard error of the indirect effect (s_ab) is given by the following equation:

In order to conduct the test, ab is divided by s_ab to yield a critical ratio that is compared with the critical value from the standard normal distribution appropriate for a given alpha level. One of the assumptions necessary for the Sobel test is that the sample size is large, so the rough critical value for the two-tailed version of the test, assuming that the sampling distribution of ab is normal and that α=.05, is ± 1.96 (Preacher & Hayes, 2004). Thus, it can be concluded that a more powerful strategy for testing mediation may be to require only (1) that there exists an effect to be mediated (i.e., c ≠ 0) and (2) that the indirect effect be statistically significant in the direction predicted by the mediation hypothesis (Preacher & Hayes, 2004).

To calculate the indirect effect according to Sobel (1982), the unstandardized regression coefficient obtained from regressing the mediator to predict the dependent variable (adjusting for the independent variable) (β=0.537) should be multiplied by the unstandardized regression coefficient obtained from regressing the independent variable to predict the mediator (β=0.803). Thus, the indirect effect of strategic orientation on organization performance through learning culture=0.537*0.803=0.431. In order to ensure that the indirect effect is significant, it is recommended to run Sobel test (Sobel, 1982). The Sobel test requires the computation of the raw regression coefficient (unstandardized coefficients) and the standard error for this regression coefficient for the association between the independent variable and the mediator (path a), and the association between the mediator and the dependent variable (adjusting for the independent variable, path b) (Pierce, 2003). The unstandardized β for path (a)=0.803 and the standard error = 0.039, and for path (b) unstandardized β=0.537 and the standard error=0.047. The data are then entered into the following program to calculate the Sobel test value.

The results revealed that the null hypothesis should be rejected and the alternative hypothesis should be accepted, since the p-value for the Sobel test (< 0.001) falls below the established alpha level of 0.05, indicating that the association between the independent variable (strategic orientation) and the dependent variable (organization performance) is reduced significantly by the inclusion of the mediator (learning culture) in the model; in other words, there is evidence of mediation. Indeed, the concept of strategic orientation focuses on conserving scarce resources, thereby consolidating strong competitive positions. It reflects the strategic directions that a firm could implement to achieve growth, sustainability, and superior performance. Strategic orientation is related to the strategic direction implemented by a firm to create the proper behaviours for the continuous superior performance of the business. Therefore, due to the uncertainty of today’s business environment, telecommunication companies in Jordan should pay attention to the importance of the strategic orientation and its dimensions that: market orientation is considered a crucial strategy that helps organizations stay competitive, and the interpretations would refer to market orientation’s role as the organization–wide generation of market information pertaining to current and future customer needs, with a key need to disseminate this information across departments, and coordinate organization–wide responsiveness to this information.

On the other hand, a firm’s technology orientation can be considered an inclination to introduce or use new technologies, products, or innovations. This suggests that customer value and the long-term success of the organization depends on new innovations, technological solutions, products, services, or processes. Moreover, technology orientation is a culture-based, firm-specific strategic orientation, consisting of complex capabilities (Alshurideh et al., 2019; Al Kurdi et al., 2020; Alshurideh et al., 2021). In addition, in response to customer needs, a firm can employ an entrepreneurial orientation in its practices and decision-making activities to improve the value of products and services. It can also be considered a continuous process leading to the creation of a sustainable competitive advantage by identifying and generating new businesses, take entrepreneurial practices, methods, process, and decision-making styles taken to act entrepreneurially. As such, if these companies adopt these strategic orientations, it will build an organizational learning culture that emphasizes the open exchange of information and ideas, in ways that facilitate learning and its creative application.

In effect, learning culture can be seen as a critical facilitator of exploiting and seizing opportunities from the surrounding dynamic environment that supports inquiry, risk-taking and experimentation, in which organizational culture is brought to play through encouraging and motivating employees’ behaviour. In fact, telecommunication companies in Jordan face more and more global, dynamic, and uncertain environments, so they need an organizational culture oriented to productive learning, to lead it to new and useful knowledge that can help it to gain opportunities and deal with risk, allowing it to fight, survive and grow. In addition, an organizational learning culture has a number of complementary benefits, such as providing employees with a sense of belonging, improving their job satisfaction, and overall effectiveness of organizational change. All these benefits increase the competitiveness of the organization. As a result of this, it will achieve a superior performance and sustainable competitive advantage. Indeed, this research study focused on the impact of strategic orientation and learning culture on the operational performance. That non-financial performance measurements focus on an organization’s long-term success, such as company image, internal business process efficiency, innovation, customer loyalty, customer satisfaction, employee satisfaction, and employee turnover. In addition, non-financial performance measures can be used to cultivate a long-term competitive advantage that depends on the organization’s strategies, objectives, vision, and mission.

Conclusion

The current research aimed to investigate the impact of strategic orientation on organizational performance, examining the mediating role of learning culture in Jordanian telecommunication companies. Based on the literature review, the research model was developed, and examined the mediating role of learning culture on the relationship. Then, the data required for this study were collected from 321 randomly sampled employees in three Jordanian telecommunication companies, Zain, Orange, and Umniah, through a paper questionnaire that was distributed to the employees in various branches of the three companies, in addition to an electronic questionnaire that was sent by email and to LinkedIn accounts. In the previous chapter, results based on specific analyses were presented. Out of these, all four of the main null hypotheses were rejected, 10 sub-null hypotheses were rejected, and three sub-null hypotheses were accepted.

The premise behind these results is that the telecommunication industry is considered to be one of the most knowledge-intensive industries, and it is believed to be a highly innovative and rapid growth sector. All these environmental changes put pressure on Jordanian telecommunication companies to improve services over time, in order to compete and survive. Accordingly, having a clear strategic orientation will enable Jordanian telecommunication companies to focus on conserving scarce resources, and paves the way for it to create the proper behaviours for the continuous superior performance, thereby consolidating strong competitive positions, growth, and sustainability. On the other hand, building a learning culture by creating continuous learning opportunities, promoting inquiry and dialogue, encouraging collaboration and team learning, creating systems to capture and share learning, empowering people towards a collective vision, connecting the organization to its environment, and having strategic leaders to support learning will help telecommunication companies to modify themselves and transform action based on new knowledge, experience, and perceptions, in order to achieve strategic objectives, thereby improving operational performance by focusing on long-term success, such as internal business process efficiency, company image, innovation, customer satisfaction, customer loyalty, employee satisfaction, and employee turnover, in order to achieve a competitive advantage, sustainability, and superior performance.

Contribution of the Study

In spite of the fact that this research was conducted based on a literature review, each of these pieces of research was conducted in different countries with different settings, where the employees behave in different ways according to their cultures, their firms’ cultures, and their countries’ cultures. Therefore, this research enables others to understand the impact of strategic orientation (market orientation, technology orientation, and entrepreneurial orientation) on organizational performance through examining the mediating role of learning culture in Jordanian telecommunication companies, where limited efforts were made to discuss this topic in this industry and in this country. Traditionally, previous research focused on studying the direct relationship between strategic orientation and organizational performance, and it devoted limited attention to studying the mediating and moderating effects of other variables on this relationship. Bing and Zhengping (2011), had suggested that there are other variables that need to be examined when studying the relationship between strategic orientation and organizational performance. Therefore, this research examined the mediating role of learning culture on this relationship between the independent and dependent variables, so this research:

• Discussed the impact of strategic orientation on organizational performance,

• Discussed the impact of strategic orientation on learning culture,

• Discussed the impact of learning culture on organizational performance,

• Explored the mediating role of learning culture on the impact of strategic orientation on organizational performance in Jordanian telecommunication companies, and the results were discussed and justified.

Indeed, Jordanian telecommunication companies should be aware that strategic orientation is considered to be closely related to learning capabilities and knowledge sharing. On the other hand, it enables information to be generated, disseminated, and ultimately transferred into knowledge for the organization. Moreover, it could be used as a way of improving the organization’s competitive performance, as well as a way to motivate the knowledge-based competitive performance of the organization, which directs organizational managers’ attention towards using strategic orientation to build the learning culture and perceive that it is vital to the immediate and future directions of the organization.

Limitations and Recommendations

• This research is limited to three Jordanian telecommunication companies (Zain, Orange & Umniah) in Amman. It didn’t include other branches of telecommunication companies, either in other cities or countries.

• The variables included in this study are strategic orientation, organizational performance, and learning culture. It did not include any other moderation or mediation variables.

• This research used three types of strategic orientation: market, technology, entrepreneurial orientation, even though there are other types of strategic orientation used in the literature.

• This research measured organizational performance using non-financial indicators, while there are other indicators to measure the organizational performance.

The following recommendations can be formulated based on the research results:

• Jordanian telecommunication companies' managers should pay more attention to strategic orientation (market orientation, technology orientation, and entrepreneurial orientation) to improve organizational performance.

• Jordanian telecommunication companies' managers should be aware that market orientation is considered a crucial strategy that helps organizations stay competitive, by focusing on its dimensions: customer orientation, competitor orientation, and inter-functional coordination.

• Jordanian telecommunication companies' managers should ensure they enhance their technological expertise to compete in their respective industries, primarily due to technological progress and the increasingly short life cycle of products and services, and ensure that customer value and a firm’s long-term success can be created through new technological solutions, innovations, production processes, or products and services.

• Jordanian telecommunication companies' managers should make sure that, in response to customer needs, a firm can employ an entrepreneurial orientation in its practices and decision-making activities to improve the value of products and services. This orientation can also be considered a continuous process leading to the creation of a sustainable competitive advantage by identifying and generating new businesses.

• Jordanian telecommunication companies' managers should be aware that firms with a learning culture are skilled at acquiring, creating, and transferring knowledge, in addition to modifying its behaviour to apply new knowledge and insights; therefore, it can improve its performance and compete. Therefore, managers must direct their attention to building a learning culture in their companies.

• Jordanian telecommunication companies' managers should ensure that their companies adopt strategic orientations and build an organizational learning culture that emphasises the open exchange of information and ideas, in ways that facilitate learning and its creative application, oriented to productive learning, in order to lead it to new and useful knowledge that can help it to gain opportunities and deal with risk, allowing them to fight, survive, and grow.

Acknowledgement

Dr. Muhammad Alshurideh, Associate Professor, The University of Jordan and University of Sharjah are the corresponding author for the paper.

References

1. Abu Zayyad, H.M., Obeidat, Z.M., Alshurideh, M.T., Abuhashesh, M., & Maqableh, M. (2020). Corporate social responsibility and patronage intentions: The mediating effect of brand credibility. Journal of Marketing Communications, 27(5), 510-533.
2. Ahmad, A., Alshurideh, M., Al Kurdi, B., Aburayya, A., & Hamadneh, S. (2021) Digital transformation metrics: A conceptual view. Journal of Management Information and Decision Sciences. 24(7) 1-18.
3. Abuhashesh, M., Al-Khasawneh, M., & Al-Dmour, R. (2019). The Impact of Facebook on Jordanian Consumers' Decision Process in the Hotel Selection. IBIMA Business Review.
4. Alaali, N., Al Marzouqi, A., Dahabreh, F., Mouzaek, E., Portal, R., & Salloum, S. (2021) The impact of adopting corporate governance strategic performance in the tourism sector: A case study in the kingdom of Bahrain. Journal of Legal, Ethical and Regulatory Issues. 24(Special Issue 1), 1-18.
5. Alameeri, K., Alshurideh, M., Al Kurdi, B., & Salloum, S.A. (2020). The effect of work environment happiness on employee leadership. International Conference on Advanced Intelligent Systems and Informatics. Springer, Cham.
6. Al-Ansaari, Y., Bederr, H., & Chen, C. (2015). Strategic orientation and business performance: An empirical study in the UAE context.Management Decision,53(10), 2287-2302.
7. Al-Dhuhouri, F.S., Alshurideh, M., Al Kurdi, B., & Salloum, S.A. (2020). Enhancing our understanding of the relationship between leadership, team characteristics, emotional intelligence and their effect on team performance: A Critical Review. International Conference on Advanced Intelligent Systems and Informatics. Springer, Cham.
8. Alkalha, Z., Al-Zu’bi, Z., Al-Dmour, H., Alshurideh, M., & Masa’deh, R. (2012). Investigating the effects of human resource policies on organizational performance: An empirical study on commercial banks operating in Jordan. European Journal of Economics, Finance and Administrative Sciences, 51(1), 44-64.
9. Alkitbi, S. S., Alshurideh, M., Al Kurdi, B., & Salloum, S.A. (2020). Factors affect customer retention: A systematic review. International Conference on Advanced Intelligent Systems and Informatics. Springer, Cham.
10. Al Kurdi, B., & Alshurideh, M. & Al afaishata, T. (2020). Employee retention and organizational performance: Evidence from banking industry. Management Science Letters, 10(16), 3981-3990.
11. Al Kurdi, B., Alshurideh, M., & Salloum, S.A. (2020). Investigating a theoretical framework for e-learning technology acceptance. International Journal of Electrical and Computer Engineering (IJECE), 10(6), 6484-6496.
12. AlMehrzi, A., Alshurideh, M., & Al Kurdi, B. (2020). Investigation of the key internal factors influencing knowledge management, employment, and organisational performance: a qualitative study of the UAE hospitality sector. International Journal of Innovation, Creativity and Change, 14(1), 1369-1394.
13. Al Mehrez, A.A., Alshurideh, M., Al Kurdi, B., & Salloum, S.A. (2020). Internal factors affect knowledge management and firm performance: a systematic review. International Conference on Advanced Intelligent Systems and Informatics. Springer, Cham.
14. Al Naqbi, E., Alshuridehb, M., AlHamadc, A., & Al, B. (2020). The impact of innovation on firm performance: a systematic review. International Journal of Innovation, Creativity and Change, 14(5), 31-58.
15. Alsharari, N.M., & Alshurideh, M.T. (2020). Student retention in higher education: the role of creativity, emotional intelligence and learner autonomy. International Journal of Educational Management.
16. AlShehhi, H., Alshurideh, M., Al Kurdi, B., & Salloum, S.A. (2020). The impact of ethical leadership on employees performance: A systematic review. International Conference on Advanced Intelligent Systems and Informatics. Springer, Cham.
17. Alshraideh, A.T.R., Al-Lozi, M., & Alshurideh, M.T. (2017). The impact of training strategy on organizational loyalty via the mediating variables of organizational satisfaction and organizational performance: An empirical study on Jordanian agricultural credit corporation staff. Journal of Social Sciences (COES&RJ-JSS), 6(2), 383-394.
18. Alshurideh, M., Al Kurdi, B., & Salloum, S.A. (2019). Examining the main mobile learning system drivers’ effects: A mix empirical examination of both the Expectation-Confirmation Model (ECM) and the Technology Acceptance Model (TAM). In International Conference on Advanced Intelligent Systems and Informatics. Springer, Cham.
19. Alshurideh, M.T., Al Kurdi, B., & Salloum, S.A. (2021). The moderation effect of gender on accepting electronic payment technology: a study on United Arab Emirates consumers. Review of International Business and Strategy.
20. Alshurideh, M., Alhadid, A.Y., & Barween, A. (2015). The effect of internal marketing on organizational citizenship behavior an applicable study on the University of Jordan employees. International Journal of Marketing Studies, 7(1), 138-145.
21. Alshurideh, M.T., Al Kurdi, B., AlHamad, A.Q., Salloum, S.A., Alkurdi, S., & Dehghan, A. (2021). Factors Affecting the Use of Smart Mobile Examination Platforms by Universities’ Postgraduate Students during the COVID-19 Pandemic: An Empirical Study. Informatics, 8(2).
22. Alshurideh, M., Masa'deh, R., & Alkurdi, B. (2012). The effect of customer satisfaction upon customer retention in the Jordanian mobile market: An empirical investigation. European Journal of Economics, Finance and Administrative Sciences, 47, 69-78.
23. Al Suwaidi, F., Alshurideh, M., Al Kurdi, B., & Salloum, S.A. (2020). The impact of innovation management in SMEs performance: a systematic review. International Conference on Advanced Intelligent Systems and Informatics. Springer, Cham.
24. Alsuwaidi, M., Alshurideh, M., Al Kurdi, B., & Salloum, S.A. (2020). Performance appraisal on employees’ motivation: A comprehensive analysis. International Conference on Advanced Intelligent Systems and Informatics. Springer, Cham.
25. Altindag, E., Zehir, C., & Acar, A.Z. (2011). Strategic orientations and their effects on firm performance in turkish family-owned firms.Eurasian Business Review,1(1), 18-36.
26. Alzoubi, H. M., Alshurideh, M., & Ghazal, T.M. (2021, June). Integrating BLE Beacon Technology with Intelligent Information Systems IIS for Operations’ Performance: A Managerial Perspective. The International Conference on Artificial Intelligence and Computer Vision. Springer, Cham.
27. Ammari, G., Alkurdi, B., Alshurideh, A., & Alrowwad, A. (2017). Investigating the impact of communication satisfaction on organizational commitment: a practical approach to increase employees’ loyalty. International Journal of Marketing Studies, 9(2), 113-133.
28. Avci, U., Madanoglu, M., & Okumus, F. (2011). Strategic Orientation and Performance of Tourism Firms: Evidence from a Developing Country.Tourism Management,32(1), 147-157.
29. Bai, N., & Fallah, Z. (2012). Relationship between Learning Culture and Organizational Performance in Iran’s Ministry of Sports and Youth. European Journal of Experimental Biology, 2(6), 2206-2211.
30. Baron, R.M., & Kenny, D. (1986). The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.
31. Bhaskar, U., & Mishra, B. (2017). Exploring Relationship between Learning Organizations Dimensions and Organizational Performance.International Journal of Emerging Markets, 12(3), 593-609.
32. Biesanz, J.C., Falk, C.F., & Savalei, V. (2010). Assessing Mediational Models: Testing and Interval Estimation for Indirect Effects. Multivariate Behavioral Research, 45(4), 661-701.
33. Bing, L.I., & Zhengping, F.U. (2011). Relationship between Strategic Orientation and Organizational Performance in Born Global: A Critical Review.International Journal of Business and Management,6(3), 109.
34. Bryman, A., & Bell, E. (2015). Business Research Methods, (4^thed). United Kingdom: Oxford University Press.
35. Chahal, H., Chahal, H., Dangwal, R. C., Dangwal, R. C., Raina, S., & Raina, S. (2016). Marketing Orientation, Strategic Orientation and their Synergistic Impact on Business Performance: A Case of SMEs in Emerging Context (India).Journal of Research in Marketing and Entrepreneurship,18(1), 27-52.
36. Cooper, A.L., Huscroft, J.R., Overstreet, R.E., & Hazen, B.T. (2016). Knowledge Management for Logistics Service Providers: The Role of Learning Culture.Industrial Management & Data Systems,116(3), 584-602.
37. Dekoulou, P., & Trivellas, P. (2015). Measuring the Impact of Learning Organization on Job Satisfaction and Individual Performance in Greek Advertising Sector.Procedia-Social and Behavioral Sciences,175, 367-375.
38. Freitas, I.M.B., Fontana, R., & Adams, P. (2013). Strategic Orientations, Marketing Capabilities and Innovation: An Empirical Investigation. In35th DRUID Celebration Conference, Barcelona, 17-19.
39. Hair, J.F., Black, W.C., Babin, B.J., & Anderson, R.E. (2010). Multivariate Data Analysis, 7^thed., New Jersey: Pearson Education, Inc.
40. Holmbeck, G.N. (2002). Post-hoc Probing of Significant Moderational and Meditational Effects in Studies of Pediatric Populations. Journal of Pediatric Psychology, 27, 87-96.
41. Hunaiti, Z., Mansour, M., & Al-Nawafleh, A. (2009). Electronic Commerce Adoption Barriers in Small and Medium-sized Enterprises (SMEs) in Developing Countries: The Case of Libya. Paper presented at the Innovation and Knowledge Management in Twin Track Economies Challenges and Solutions - Proceedings of the 11th International Business Information Management Association Conference.
42. Kim, K., Watkins, K.E., & Lu, Z. (2017). The Impact of a Learning Organization on Performance: Focusing on Knowledge Performance and Financial Performance.European Journal of Training and Development,41(2), 177-193.
43. Kurdi, B., Alshurideh, M., & Alnaser, A. (2020). The impact of employee satisfaction on customer satisfaction: Theoretical and empirical underpinning. Management Science Letters, 10(15), 3561-3570.
44. Lim, B.T., Wang, Z., & Oo, B.L. (2016). Change Management for Sustainable Competitive Advantages: The Roles of Organisational Culture and Employees in the Chinese Construction Firms.International Journal of Sustainable Building Technology and Urban Development,7(3-4), 230-236.
45. MacKinnon, D.P., Fairchild, A.J., & Fritz, M.S. (2007). Mediation Analysis. Annual Review of Psychology, 58, 593-614.
46. Malik, P., & Garg, P. (2017). The Relationship between Learning Culture, Inquiry and Dialogue, Knowledge Sharing Structure and Affective Commitment to Change.Journal of Organizational Change Management,30(4).
47. Marsick, V.J., & Watkins, K.E. (2003). Demonstrating the Value of an Organization's Learning Culture: The Dimensions of the Learning Organization Questionnaire.Advances in Developing Human Resources,5(2), 132-151.
48. Masa’deh, R., Alananzeh, O., Tarhini, A., & Algudah, O. (2018). The Effect of Promotional Mix on Hotel Performance during the Political Crisis in the Middle East. Journal of Hospitality and Tourism Technology, 9(1), 32-47.
49. Masa'deh, R., Obeidat, B., & Tarhini, A. (2016). A Jordanian empirical study of the associations among transformational leadership, transactional leadership, knowledge sharing, job performance, and firm performance: A structural equation modelling approach. Journal of Management Development, 35(5), 681-705.
50. Masa’deh, R., Shannak, R., & Maqableh, M. (2013). A Structural Equation Modeling Approach for Determining Antecedents and Outcomes of Students’ Attitude toward Mobile Commerce Adoption. Life Science Journal, 10(4), 2321-2333.
51. Moh'd Taisir Masa'deh, R., Shannak, R.O., & Mohammad Maqableh, M. (2013). A Structural Equation Modeling Approach for Determining Antecedents and Outcomes of Students' Attitude toward Mobile Commerce Adoption. Life Science Journal, 10(4), 2321-2333.
52. Mu, J., & Di Benedetto, C.A. (2011). Strategic Orientations and New Product Commercialization: Mediator, Moderator, and Interplay.R&D Management,41(4), 337-359.
53. Naqvi, R., Soomro, T.R., Alzoubi, H.M., Ghazal, T.M., & Alshurideh, M.T. (2021). The nexus between big data and decision-making: A study of big data techniques and technologies. In The International Conference on Artificial Intelligence and Computer Vision. Springer, Cham.
54. Nasir, W., Al Mamun, A., & Breen, J. (2017). Strategic Orientation and Performance of SMEs in Malaysia.SAGE Open,7(2).
55. Nuseir, M.T., Aljumah, A., & Alshurideh, M.T. (2021). How the Business Intelligence in the New Startup Performance in UAE During COVID-19: The Mediating Role of Innovativeness. The Effect of Coronavirus Disease (COVID-19) on Business Intelligence, 334, 63-79.
56. Obeidat, B. (2016). The Effect of Strategic Orientation on Organizational Performance: The Mediating Role of Innovation.International Journal of Communications, Network and System Sciences,9(11), 478.
57. Obeidat, B., Al-Hadidi, A., & Tarhini, A. (2017a). Factors Affecting Strategy Implementation: A Case Study of Pharmaceutical Companies in the Middle East. Review of International Business and Strategy, 27(3), 386-408.
58. Obeidat, Z.M., Alshurideh, M.T., & Al Dweeri, R. (2019). The Influence of Online Revenge Acts on Consumers Psychological and Emotional States: Does Revenge Taste Sweet? Paper presented at the Proceedings of the 33rd International Business Information Management Association Conference, IBIMA 2019: Education Excellence and Innovation Management through Vision 2020, 4797-4815.
59. Obeidat, U., Obeidat, B., Alrowwad, A., Alshurideh, M., Masadeh, R., & Abuhashesh, M. (2021). The effect of intellectual capital on competitive advantage: the mediating role of innovation. Management Science Letters, 11(4), 1331-1344.
60. Obeidat, B., Tarhini, A., & Aqqad, N. (2017b). The Impact of Intellectual Capital on Innovation via the Mediating Role of Knowledge Management: A Structural Equation Modeling Approach. International Journal of Knowledge Management Studies, 8(3/4), 273-298.
61. Odeh, R.B.M., Obeidat, B.Y., Jaradat, M.O., & Alshurideh, M.T. (2021). The transformational leadership role in achieving organizational resilience through adaptive cultures: the case of Dubai service sector. International Journal of Productivity and Performance Management.
62. Onyema, E.O. (2014). Effects of Entrepreneurial Orientations on Organizational Learning in a Manufacturing Firm in Nigeria.International Journal of Business Administration,5(2), 94.
63. Osman Zainal Abidin, J. (2014). An empirical investigation into the significance of intellectual capital and strategic orientations on innovation capability and firm performance in Malaysian Information and Communications Technology (ICT) Small-to-Medium Enterprises (SMEs). Doctor of Philosophy (PhD),Management,RMIT University, Melbourne, Australia.
64. Peat, J., Mellis, C., Williams, K., & Xuan W. (2002).Health Science Research: A Handbook of Quantitative Methods. London: Sage.
65. Pokharel, M.P., & Choi, S.O. (2015). Exploring the Relationships between the Learning Organization and Organizational Performance.Management Research Review,38(2), 126-148
66. Preacher, K.J., & Hayes, A.F. (2004). SPSS and SAS Procedures for Estimating Indirect Effects in Simple Mediation Models. Behavior Research Methods, Instruments, and Computers, 36(4), 717-731.
67. Radhakrishna, R.B. (2007). Tips for Developing and Testing Questionnaires/Instruments. Journal of Extension, 45(1).
68. Real, J.C., Roldán, J.L., & Leal, A. (2014). From entrepreneurial orientation and learning orientation to business performance: Analyzing the mediating role of organizational learning and the moderating effects of organizational size.British Journal of Management,25(2), 186-208.
69. Santos-Vijande, M.L., Sanzo-Perez, M.J., Alvarez-Gonzalez, L.I., & Vazquez-Casielles, R. (2005). Organizational learning and market orientation: Interface and effects on performance.Industrial Marketing Management,34(3), 187-202.
70. Sarker, S., & Palit, M. (2015). Strategic orientation and performance of small and medium enterprises in Bangladesh.International Journal of Entrepreneurship and Small Business,24(4), 572-586.
71. Sekaran, U., & Bougie, R. (2013). Research Methods for Business (6th ed.). United Kingdom: John Wiley & Sons Ltd.
72. Shah, S.F., Alshurideh, M., Al Kurdi, B., & Salloum, S.A. (2020). The impact of the behavioral factors on investment decision-making: A systemic review on financial institutions. In International Conference on Advanced Intelligent Systems and Informatics. Springer, Cham.
73. Sobel, M.E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. In S. Sociological Methodology 1982. San Francisco: Jossey-Bass.
74. Song, J.H., Joo, B.K., & Chermack, T.J. (2009). The Dimensions of Learning Organization Questionnaire (DLOQ): A validation study in a Korean context.Human Resource Development Quarterly,20(1), 43-64.
75. Stephen, I.A., Oluseye, O.O., & Abolaji, A.J. (2017). Extending the knowledge strategy concept: Linking organizational knowledge with strategic orientations. Academy of Strategic Management Journal, 16(3).
76. Tarhini, A., Mgbemena, C., & Trab, M.S.A. (2015). User adoption of online banking in Nigeria: A qualitative study. Journal of Internet Banking and Commerce, 20(3).
77. Thoumrungroje, A., & Racela, O. (2013). The contingent role of customer orientation and entrepreneurial orientation on product innovation and performance. Journal of Strategic Marketing, 21(2), 140-159.
78. Tomal, D.R., & Jones, K.J. (2015). A comparison of core competencies of women and men leaders in the manufacturing industry.The Coastal Business Journal,14(1), 13.
79. Tseng, S.M., & Lee, P.S. (2014). The effect of knowledge management capability and dynamic capability on organizational performance.Journal of Enterprise Information Management,27(2), 158-179.
80. Van Teijlingen, E., & Hundley, V. (2002). The importance of pilot studies.Nursing Standard, 16(40), 33.
81. Wahda, W. (2017). Mediating effect of knowledge management on organizational learning culture in the context of organizational performance. Journal of Management Development, 36(7), 846-858.
82. Wang, Q., Wang, Z., & Zhao, X. (2015). Strategic orientations and mass customization capability: The moderating effect of product life cycle.International Journal of Production Research,53(17), 5278-5295.
83. Wheelen, T.L., & Hunger, J.D. (2017).Strategic management and business policy. Pearson.
84. Williams, B., Brown, T., & Onsman, A. (2010). Exploratory factor analysis: A five-step guide for novices. Australasian Journal of Paramedicine, 8(3), 1-13.
85. Yu, T., & Chen, C.C. (2012). A study on the relationship between organizational learning culture and organizational performance in Taiwan's university and college libraries. Journal of Educational Media & Library Sciences, 50(2).
86. Zehir, C., Can, E., & Karaboga, T. (2015). Linking entrepreneurial orientation to firm performance: The role of differentiation strategy and innovation performance.Procedia-Social and Behavioral Sciences,210, 358-367.