Keywords

Digital Technology, Decision-Making, Knowledge Sharing, Employee Dynamics, Employee Job Performance.

Introduction

In the current digital era, the widespread reliance on technology, particularly within the digital environment, has become an integral aspect of modern life. This phenomenon spans all age groups, from young schoolchildren to experienced managers. Individuals across the spectrum are now embracing tools like ChatGPT and Google Bard, among other AI-driven platforms, to meet their daily knowledge acquisition needs and offer vital support. Furthermore, integrating digital technology has brought about transformative changes in communication and coordination paradigms.

Notably, adopting virtual teams, WhatsApp, ERP systems, and similar innovations has significantly bolstered the effectiveness of interpersonal interactions. These technologies have greatly improved individuals' ability to communicate and coordinate efficiently by seamlessly delivering relevant information exactly when needed. This newfound capability is crucial in a world that relies on timely and accurate information dissemination.

Social media usage is necessary in this technological age to improve cooperation and communication. Organizations use social media as a communication channel for different purposes (Lee et al., 2021). Knowledge availability is extremely important resource for organizations (van den Hooff & de Ridder, 2004) pointed out that knowledge sharing is a form of communication. Effectiveness of communication can be leveraged with the use of technology-driven platforms like the company's own applications, which are used by the employees exclusively, and common platforms like Zoom, Microsoft, etc.

Strong and efficient employee coordination is essential to keep everyone updated on progress and any related concerns as they develop (Al Nahyan et al., 2019). Good coordination ensures that all departments use the organizations’ resources judiciously and better coordination improves the efficiency of the employees. The effectiveness of an organization's overall performance depends on the coordination of its decision-makers, each of whom oversees a particular component of a larger decision-problem.

Engaging in the digital environment can facilitate the enhancement of one's personality, potentially shifting an introverted disposition towards extroversion. Popular social media platforms, say, Instagram, WhatsApp, and the like contain a wealth of information. This information-rich environment has the potential to influence an individual's personality in numerous ways. By examining the impacts of these technologies on knowledge acquisition, dissemination, and collaborative endeavors, we strive to provide valuable insights into the evolving landscape of human interactions in the digital age. (Khalid et al., 2023) emphasized digital transformation as a cultural shift, necessitating new IT infrastructure and digital skill sets across organizations, aligning with the impact of digital technologies on employee dynamics. The adoption of agility principles to enhance innovation in organizations, resonating with the need for agile practices in the context of digital technology-driven employee dynamics.

This research article explores the intricate interplay between contemporary digital tools, communication dynamics, coordination mechanisms, and individuals' personality traits. We investigate how digital technology influences the coordination and communication among individuals. Furthermore, we explore how this enhanced coordination and communication contribute to knowledge sharing, subsequently impacting decision-making processes. Additionally, we examine how these processes of knowledge sharing and decision-making positively influence an individual's job performance within the workplace.

Literature Review

Digital Technology Driven Coordination and Knowledge Sharing

Virtual teams positively and significantly affect knowledge sharing and enhance job performance (Pangil & Moi Chan, 2014). In virtual teams, members are often geographically dispersed, making face-to-face interactions challenging. Digital tools and platforms have bridged this gap, enabling seamless communication, collaboration, and information exchange. These tools expedite the recognition, coordination, and utilization of specialized knowledge within virtual teams. As a result, team members can more efficiently pool their expertise, leading to better- informed decision-making and task execution, ultimately improving job performance in the virtual team setting. Effective coordination is a critical factor for successful knowledge sharing within virtual teams, which ultimately contributes to the job performance.

H₁: Digital technology-driven coordination positively influences an individual's knowledge sharing activity.

Digital Technology Driven Coordination and Decision Making

Adopting digital tools such as online analytics, artificial intelligence, and data-driven decision-making systems in industries will likely enhance coordination among professionals. This improved coordination can lead to faster access to relevant information, and better collaboration. When the tasks are complex and require high velocity of information exchange, it is important and critical to have good coordination among the team members (Chiocchio, 2007). This is required when decisions have to be made which require deep understanding of the issues to be resolved. Coordination is very important for tasks that depend on each other and are done by different team members (Wittenbaum et al. 2002). Individuals within teams may be better equipped to make informed and timely decisions, ultimately benefiting from the positive influence of digital technology-driven coordination.

H₂: Digital technology-driven coordination positively influences an individual's decision- making activity.

Digital Technology Driven Communication and Knowledge Sharing

Technology has revolutionized the way teams work together and carry out their tasks. Although traditional in-person team interactions are still common, virtual teams that convene via email or computer conferences are growing in popularity (Baltes et al., 2002). Communication refers to spoken interactions between people as well as body language (Ismail Al-Alawi et al., 2007). Social networking has a tremendous positive impact on human connection in the workplace. This kind of communication is essential for promoting the transfer of knowledge. From a functional perspective, communication facilitates the exchange of knowledge (Michailova & Sidorova, 2011), which fosters organizational learning. A notable example of this theoretical approach is pointed out by (Schwartz, 2007), who explored the effects of employing various communication platforms for knowledge exchange.

H₃: Digital technology-driven communication positively influences an individual's knowledge sharing activity.

Digital Technology Driven Communication and Decision Making

Applications in crucial business decisions including product development, profitability, brand management, customer relationship management, buying and selling, and communication have been significantly impacted by digital technology (Dahiya, 2018). Effective multilateral communication and agreement are necessary for many of the daily transactions in the workplace. Democratic political decision-making at the municipal or federal levels requires complicated, nearly invariably multilateral communication (Vragov & Kumar, 2013). Communication is extremely important for the decision making in an organization. (Pangil & Moi Chan, 2014) found that communication with the teams with the help of digital technologies has enabled decision making and knowledge sharing among the employees.

H₄: Digital technology-driven communication positively influences an individual's decision making activity.

Digital Technology Driven Personality and Knowledge Sharing

Individual dispositions towards sharing prior experiences and engaging in tacit knowledge- sharing activity are directly influenced by personality factors (Borges, 2012). The Big Five personality qualities significantly predict knowledge creation and sharing. Different priorities for social connection and active engagement include extraversion, whose attribute conjures up images of warmth, friendliness, joy, and assertiveness. Extroverts are sociable and talkative, which improves the likelihood that they will share knowledge with their coworkers within the boundaries of their jobs (Cui, 2017).

People with extrovert personalities tend to be emotionally upbeat and enjoy teamwork (Farrukh et al., 2019). Knowledge sharing is much more likely to be successful and effective in environments where extroversion is high (Wadhwa & Bali, 2016) findings show a strong and positive relationship between extraversion alongside knowledge sharing knowledge.

H₅: Extravert personality traits with the help of digital technology positively influence knowledge sharing.

Digital Technology Driven Personality and Decision Making

Performance is impacted by the decisions managers make and the outcomes of their decision- making process (Amason, 1996). An important influence on the quality of decisions is exerted by both external and internal elements in a dynamic and flexible decision-making process (Erjavec et al., 2019). Personality qualities and domain knowledge are among the most notable internal influences. (Oehler et al., 2018) found that extraversion and neuroticism influence decision-making most among the Big five personality traits. Extroverts typically make quick decisions based on instinct and what feels right.

H₆: Extraversion personality traits help of digital technology positively influence decision-making.

Knowledge Sharing and Decision Making

Making decisions in an organization demands an immense amount of knowledge because decisions are dependent on an individual's expertise. Having content knowledge required to make a particular decision develops the capability to make significant decisions well (McKenzie et al., 2011). (Lin & Lee, 2004) found that it is essential for managers, who are important decision makers in an organization to cultivate the habit of knowledge sharing. In an organization where decision making is involved, collaborative culture, and habits of knowledge sharing play a significant role in influencing them (Nugroho, 2018; (Li et al., 2019) emphasize the importance of aligning resources, organizational structures, and cultural elements to effectively adopt Industry 4.0 for maximizing information and knowledge sharing. The integration of IT systems is crucial to meeting information requirements and supporting decision-making processes.

H₇: Digital technology enhanced knowledge sharing positively influences decision-making.

Knowledge Sharing and Job Performance

Creating a knowledge-sharing environment where employees may share newly acquired knowledge and give others access to intellectual resources useful for job performance is one way to build a successful organization. Knowledge sharing among staff is essential for organizational effectiveness (e.g., knowledge adoption, innovation). In order to increase productivity and standardize operations in complex distributed businesses, data and knowledge exchange is critical (Al Nahyan et al., 2019). Technology is said to play a crucial part in knowledge sharing among members of international teams. This technology includes the internal platforms the company uses for the smooth functioning of the organization as well as social media platforms the company uses to manage relationships effectively and improve their corporate image. Social media can be combined with other media tools, such as audio, video, or images, as well as numerous communication tools, such as chat applications, audio/video conferencing programs, or feedback systems. (Nezafati et al., 2023) highlights the impact of Knowledge Management Systems (KMS) software, particularly the user experience, in shaping individuals' inclination toward knowledge sharing. Notably, the KMS reward system and active engagement of top management substantially enhances user engagement in knowledge sharing activities. These findings are pivotal in comprehending the manner in which digital technology-driven employee dynamics, specifically within knowledge-sharing paradigms, and it can elevate job performance by facilitating efficient generation, assessment, and utilization of knowledge assets in the digital realm.

H₈: Digital technology enhanced knowledge sharing positively influences job performance.

Decision Making and Job Performance

The process of choosing the most effective course of action from a range of options can be used to operationalize the idea of decision-making (Sun, 2017). The way that groups operate and make choices has changed as a result of changes in the business environment, including growing globalization, offshore outsourcing, rising travel expenses, the rise of mobile work, and the necessity for quick decisions as a group (Turban et al., 2011); (Xia et al., 2024) explore the influence of the digital economy and emphasizes advancements in digital technologies and the transformative potential of block chain. These innovations improve service quality, secure transactions, and drive global digitalization, offering insights into potential impacts on employee dynamics and job performance within technology-driven organizations. Combining efficient decision-making with an electronic communication network would enable flexible information sharing across functional boundaries, which can boost performance (Mohamad et al., 2017); (Balicka, 2023) has shown how innovations like Big Data, IoT, Cloud Computing, and Machine Learning, notably LSTM networks, revolutionize decision-making. These technologies amplify data collection, forecasting accuracy, and real-time analysis, shaping dynamic decision-making landscapes. They form a pivotal nexus, elucidating the profound influence of digital tools on employee dynamics and job performance, primarily mediated through enriched and data-driven decision processes.

H₉: Digital technology enhanced decision-making positively influences job performance.

Theoretical Framework

Theoretical framework developed herein is an outcome of our comprehensive literature review, encapsulating an exploration of the impact of digital technology-driven coordination, communication, and personality traits on employee job performance within organizational settings. The independent variables, encompassing digital technology-facilitated coordination, communication, and individual personality traits, are anticipated to impact knowledge-sharing mechanisms and employee decision-making processes. It is hypothesized that these mediating variables play pivotal roles in shaping and determining the resultant job performance of individuals within the organizations. The framework posits that the adoption and integration of digital tools and platforms significantly contribute to how employee’s coordination disseminate information through communication channels and defines employees' personality. These factors collectively drive the flow of knowledge and decision-making dynamics, ultimately impacting the overall job performance of employees within organizational contexts. Figure 1 shows the theoretical framework of the research.

Methodology

The primary objective of this study is to explore the impact of digital technology-driven employees' coordination, communication, and personalities on knowledge sharing and decision-making, ultimately aiming to enhance employee job performance. To achieve this goal, a quantitative survey-based approach is chosen for its suitability in confirming the hypotheses generated in the research model. The utilization of real-world data is crucial to test and validate the specific relationships identified in the study.

The target population for this study is the IT industry across Pan India. India's IT sector is important nationwide, with key hubs spread nationwide. The industry's impact extends beyond regional boundaries, contributing substantially to India's economy and global technological advancement. Esteemed institutions such as the Indian Institute of Science (IISc) and initiatives like Startup India further bolster the ecosystem supporting the IT industry across the country. This substantiates its selection as the optimal setting for the research investigating the influence of digital technology on the performance of job among IT employees. The sample size collected was 200. The collected dataset underwent screening checks for missing values and outliers, removing 20 cases and leaving 180 valid responses for statistical analysis.

The research data were gathered through a questionnaire designed based on a comprehensive literature review. Responses were collected from executive-level employees, associate professionals, managers, and administrators working in IT industries, aligning with the study's objectives. The study utilized the partial least squares-structural equation modeling (PLS-SEM) method. Subsequently, the collected data underwent further examination for reliability and validity, utilizing the PLS-SEM method.

The research model is founded on the research gap outlined by (Deng et al., 2023) in their study conducted in Australia. However, the study focuses on the IT sector in India. Unlike (Deng et al., 2023) research, which delves into the Australian context, the choice of location of this research reflects the distinct work culture and digital technology utilization in India. Building upon the insights gained from (Shah & Barker, 2017), which emphasized the significance of cultural norms in workplace misunderstandings between Indian and Australian cultures, this research study introduced an additional variable—personality—in the model, Table 1.

Table 1 shows the constructs and questionnaires used for the research and the sample collection.

Table 1 Constructs and Questionnaires
CONSTRUCT	ITEM	SOURCE
Coordination (C)	C1 Digital technologies helps to harmonize operations at work. C2 Digital technologies helps to coordinate operations at work. C3 Digital technologies support tasks associated with work. C4 Digital tools facilitate the expression of problems and concerns.	(Deng et al., 2023)
Communication (CM)	CM1 Make frequent use of digital technology for communication. CM2 Communicate in spontaneous meetings, phone conversations. CM3 Make effective use of digital technology for communication. CM4 Openly share ideas and information using digital technologies. CM5 Little concerned with the openness of the information flow when using digital technologies.	(Deng et al., 2023)
Knowledge Sharing (K)	K1 Embrace digital technologies to routinely share knowledge. K2 Embrace digital technologies to routinely seek knowledge. K3 Embrace digital technologies to routinely share ideas openly. K4 The team focuses at using the knowledge of its members. K5 Coworkers are eager to use digital technologies to assist others. K6 Coworkers don't share their greatest ideas.	(Deng et al., 2023)
Decision Making (D)	D1 Digital technologies helps me by providing relevant information. D2 Digital technologies helps me by providing timely information. D3 Digital technologies helps me by providing accurate information. D4 Digital technologies helps me to improve communication. D5 Digital technologies helps me by facilitating interactions between stakeholders. D6 Digital technologies helps me to deal with the complexity.	(Deng et al., 2023)
Personality (P)	P1 I am a leader. P2 I am persuasive. P3 I am self-motivated. P4 I am energetic.	(Yang & Hwang, 2014)
Job Performance	JP1 I execute the tasks assigned to me. JP2 I meet formal performance standards. JP3 I execute all required responsibilities. JP4 I never skip the obligated aspects of the job. JP5 I consistently perform essential duties.	(Deng et al., 2023)

Measurement Model

This research paper utilizes SmartPLS4 software to assess the reliability and validity of the constructs. The Cronbach’s alpha, and composite reliability of all constructs were above 0.7 as per (Al-Emran et al., 2019) meeting the minimum criteria for reliability. Construct validity is evaluated through two measures: Convergent validity, assessed by the average variance extracted (AVE) test, and Discriminant validity analysis, employing the Fornell and Larcker criterion technique.

The Ave & Discriminant Validity

The convergent validity criteria necessitate that the minimum value of AVE is above 0.5 (Hair et al., 2020); (Cheah et al., 2018). In our analysis, the AVE values exceeded 0.5, thereby satisfying the convergent validity criteria. The results of the data analysis indicate that all construct values are not only satisfactory but also valid. The outcomes of the measurement model affirm the appropriateness of using these constructs for structural relationship analysis Table 2.

Table 2 Measurement Model
Construct	Items	Item loadings	Average variance extracted (AVE)	Cronbach's alpha	Composite reliability
Coordination	C1	0.751	0.629	0.801	0.871
	C2	0.870
	C3	0.827
	C4	0.716
Communication	CM1	0.818	0.565	0.797	0.862
	CM2	0.750
	CM3	0.826
	CM4	0.835
	CM5	0.462
Decision Making	D1	0.725	0.552	0.837	0.880
	D2	0.790
	D3	0.648
	D4	0.785
	D5	0.802
	D6	0.693
Job Performance	JP1	0.840	0.728	0.907	0.931
	JP2	0.809
	JP3	0.900
	JP4	0.851
	JP5	0.865
Knowledge Sharing	K1	0.809	0.591	0.860	0.896
	K2	0.807
	K3	0.755
	K4	0.793
	K5	0.780
	K6	0.656
Personality	P1	0.782	0.593	0.769	0.852
	P2	0.635
	P3	0.776
	P4	0.869

Tables 2 and 3 show the AVE and discriminant validity measurements.

Table 3 Discriminant Validity Using Fornell and Larcker Method
Construct	C	CM	D	JP	K	P
Coordination	0.793	0	0	0	0	0
Communication	0.509	0.751	0	0	0	0
Decision Making	0.503	0.608	0.743	0	0	0
Job Performance	0.534	0.445	0.573	0.853	0	0
Knowledge Sharing	0.494	0.693	0.706	0.533	0.769	0
Personality	0.339	0.304	0.438	0.592	0.406	0.770

In structural equation modelling (SEM), the reliability and validity of measurement models heavily rely on the strength of item loadings. (Bagozzi & Yi, 1988) underscore that loadings below approximately 0.5 might imply that the item isn't adequately capturing the underlying construct. Additionally, extremely high loadings exceeding about 0.95 suggest potential issues with multi-colinearity or the possibility that the item is overly specific to the construct, possibly indicating redundancy within the model. Therefore, researchers often aim for factor loadings between these thresholds to ensure that the items both reliably measure the construct and remain distinct from other variables in the model. Adhering to Bagozzi and Yi's guidelines, item loadings above approximately 0.5 are indicative of a robust relationship between the surveyed items and their respective constructs. Our findings revealed that the majority of item loadings fell within the threshold, between 0.5 and 0.95, signifying a strong association between the surveyed items and their intended constructs. This notably supported the reliability and validity of our measurement model, contributing to the overall robustness of our study's findings and conclusions.

Structural Model

The structural equation modelling (SEM) is used to analyze the relationship between the constructs. The hypothesized path coefficients were estimated using the PLS-SEM algorithm technique using Smart PLS 4 software. (Hult et al., 2018) guidelines on the path (β) coefficient values vary from –1 (strong negative relationship) to +1 (strong positive relationship). The bootstrapping process is used to estimate the path coefficient by drawing many sub-samples from the original sample, which is also called bootstrapped sub-samples with replacement. The bootstrap samples with no sign change option are executed through Smart PLS software for path analysis estimation. The hypothesis testing using Smart PLS, the t-values should be above 1.97 (Hult et al., 2018). The structural model path analysis model found that all the hypothesized paths are significant except H1, H2, and H3.

Table 4 shows the path coefficient values of all the hypothesized relationships.

Table 4 Path Coefficients
Path	Hypotheses	Coefficient (β)	P value	P Value	T statistics	Supported / Not Supported
C -> D	H1	0.137	0.055	> 0.05	1.921	Not supported
C -> K	H2	0.144	0.075	> 0.05	1.782	Not supported
CM -> D	H3	0.179	0.101	> 0.05	1.640	Not supported
CM -> K	H4	0.564	0.000	< 0.05	8.298	Supported
D -> JP	H5	0.392	0.000	< 0.05	4.423	Supported
K -> D	H6	0.451	0.000	< 0.05	4.443	Supported
K -> JP	H7	0.257	0.010	< 0.05	2.589	Supported
P -> D	H8	0.155	0.013	< 0.05	2.490	Supported
P -> K	H9	0.186	0.002	< 0.05	3.030	Supported

The relationship of Coordination towards Decision making (H1), and Knowledge sharing (H2) is not significant at ρ = > 0.05, with ρ-value greater than 0.05. The path Communication towards Decision making (H3) is not significant at ρ = > 0.05. The path Communication towards Knowledge sharing (H4) is significant at ρ = < 0.05 with β = 0.564. The path Decision making towards Job performance (H5) is significant at ρ = < 0.05 with β = 0.392. The relationship of Knowledge sharing towards Decision making (H6) and Job performance (H7) is significant at ρ = < 0.05 with β = 0.451, and 0.257 respectively. The path Personality towards Decision making (H8), and Knowledge sharing (H9) is significant at ρ = < 0.05 with β = 0.155, and 0.186 respectively. Table 4 shows the path coefficients (coefficients, p-values, T-statistics).

The coefficient of determination (R2) explains the impact of the overall effect of exogenous variables on endogenous variables. R-square is defined as a measure of the model's predictive accuracy and is calculated as the squared correlation between a specific endogenous construct's actual and predicted values. The R-square values of Decision making are 0.554, Knowledge Sharing is 0.529, and Job performance is 0.355. The R-squared value suggests that 35.5% of the variability in job performance can be attributed to the combined effects of decision-making and knowledge sharing. Similarly, 52.9 % of the variability in knowledge sharing can be attributed to the combined effects of Communication and Personality, and 55.4 % of the variability in Decision making can be attributed to the combined effects of Communication, Personality, and Knowledge sharing.

Results and Discussions

In examining digital technology-driven coordination, communication, and personality in relation to decision-making, knowledge sharing, and overall employee job performance, several key findings emerged. This study discovered that digital technology-driven coordination doesn't significantly impact knowledge sharing or decision-making; communication plays a crucial role in enhancing knowledge sharing. This correlation between knowledge sharing and decision-making positively influences employee job performance.

Digital technology-driven coordination has potential challenges in coordinating tasks across teams or departments. Effective collective coordination among employees may require specialized tools for collaborative work. Recognizing these limitations, there's a possibility that these tools might not seamlessly facilitate collective coordination, impacting overall collaborative effectiveness despite individual performance excellence.

The flow of information through digital channels positively influences knowledge sharing, indicating communication's vital role in fostering an environment conducive to sharing knowledge. While increased knowledge-sharing practices were observed, the impact on improved decision-making remained limited. Individuals who frequently communicate through digital technologies and openly share ideas and information, both directly and personally, have experienced greater knowledge sharing. However, this hasn't further facilitated improved decision-making in their workplace. Nevertheless, habitual knowledge sharing practices aided in providing timely and relevant information, fostering better stakeholder interaction. (Bergum Johanson et al., 2023) show that gender exhibited an even distribution in digital communication competence, possibly due to equal exposure to digital tools and platforms during upbringing and education for both men and women. Employees need to understand the importance of upskilling and enhancing their competence in digital technology to thrive in the IT industry.

Employees who exhibit extraversion traits perceive these qualities as influential in their utilization of digital platforms for knowledge sharing and decision-making. Personality traits significantly shape how we share knowledge and make decisions in the digital realm, ultimately impacting job performance. Traits like extraversion drive individuals to share more and actively engage in decision-making through digital platforms. Identifying these traits during hiring helps create teams that collaborate effectively, enhancing knowledge sharing and decision-making in digital environments. Their leadership, persuasiveness, self-motivation, and high energy levels contribute to steering discussions, persuading others, independently driving projects, and fostering engagement during digital interactions, thereby influencing their effectiveness in using digital platforms for collaboration. Their ability to persuade others is pivotal in presenting ideas convincingly, securing agreement, and influencing decisions in digital discussions or meetings. Their self-motivation drives them to independently advance projects within digital platforms, ensuring swift and efficient completion of tasks. Finally, their high energy levels exhibit enthusiasm during digital interactions, fostering engagement and sustaining momentum in collaborative efforts.

When employees improve their knowledge sharing, it leads to smarter decision-making. Accessing a broader pool of information sparks diverse perspectives and valuable insights, enriching the decision-making process. This collective wisdom positively shapes decisions within the digital workspace. Cultivating a strong culture of sharing knowledge enables employees to access the information they need quickly. This swift access to data accelerates decision-making, empowering employees to respond promptly to challenges and capitalize on opportunities in the digital landscape. Increased knowledge sharing also helps them identify potential decision-making pitfalls. With various information and viewpoints available, employees can detect and address risks early, ensuring more robust and secure decisions. Moreover, effective knowledge sharing naturally aligns decisions with the company's goals, vision, and long-term plans. The ongoing knowledge exchange nurtures a culture of innovation and creativity in the digital workspace. Diverse ideas and perspectives stemming from knowledge-sharing platforms often foster innovative solutions and creative approaches in decision-making processes. Knowledge sharing actively involves everyone in decision-making. When well-informed and engaged, stakeholders're more inclined to participate in decision-making discussions, contributing valuable insights and enriching the conversations.

Knowledge sharing is pivotal in enhancing overall job performance across various dimensions. As revealed in the literature and supported by the analysis, when employees engage in effective knowledge sharing practices, several positive outcomes contribute to improved job performance. Firstly, it cultivates a culture of continuous learning. When everyone shares tips, tricks, and insights, it perpetuates an ongoing learning environment. People stay updated with the latest trends, new methods, and industry tech, significantly boosting their skills and expertise. Secondly, it is all about teamwork and collaboration. Sharing knowledge helps team members understand each other's strengths and perspectives better, enhancing collaboration. Thirdly, knowledge sharing significantly impacts decision-making processes and offers a platform for fresh ideas and problem-solving.

Effective decision-making has a substantial impact on job performance across different dimensions. When individuals make informed and timely decisions, it significantly improves task execution, enhancing overall productivity. Besides, well-thought-out decisions help minimize errors and risks, ultimately elevating the quality of work delivered. In addition, informed decision-making aligns tasks with strategic goals, ensuring that each effort contributes to broader organizational objectives. This research discovered a positive correlation between accurate decision-making and job performance metrics. Employees who demonstrated proficiency in decision-making showcased higher productivity, fewer errors, and better alignment with our organizational goals. Consequently, decision-making is critical in cultivating a work environment that fosters productivity, efficiency, and successful goal achievement.

Participants view job performance comprehensively, aligning it with specific duties, formal requirements, and essential role aspects. Their responses highlight a strong commitment to meeting formal expectations and consistently executing duties without neglect, emphasizing a conscientious approach to job performance. Effective communication, leveraging personality strengths, knowledge sharing, data-driven decisions, and utilizing digital tools positively contribute to overall job performance. This comprehensive view of job performance goes beyond task completion, encompassing communication, knowledge sharing, decision-making, and resource utilization to achieve optimal outcomes in their roles.

Managerial Implications

Recognizing the significant impact of communication on knowledge sharing, managers should prioritize enhancing communication platforms that foster open dialogue and seamless information exchange among teams. Managers adopting collaborative platforms like Microsoft Teams or Slack can facilitate quick sharing of insights, ideas, and information, encouraging a culture of knowledge exchange. In addition to this, implementing recognition programs for employees contributing to knowledge sharing initiatives and providing accessible sharing platforms can further cultivate a knowledge sharing culture in the organization. Managers can utilize tools such as Zoom and Google Meet, which enhance communication by allowing face-to-face interactions and visual cues. Platforms like Yammer or Workplace by Facebook can facilitate cross-departmental knowledge exchange. Tools such as chatbots and virtual assistants aid in information retrieval based on readily available data to expedite decision-making in their daily operations. Also, personality analysis tools like Crystal or Traitify can improve information exchanges by enhancing team dynamics and understanding.

To enhance the knowledge sharing of employees, managers can invest in learning management systems for continuous employee learning, which equips them to leverage technology effectively for improved knowledge sharing and decision-making. (Paasivaara et al., 2008) discussed the transition to a hybrid work culture post-COVID-19, where leveraging teleconferencing, chat platforms, web cameras, and tools like Scrum or Kanban, notably improved communication, trust, motivation, and interaction quality, particularly in distributed projects where geographical and cultural barriers hindered effective communication. This has facilitated one-to-one interaction and enhanced communication by allowing visual cues and improving understanding and clarity during discussions.

In the contemporary world, achieving smoother interaction between teams during a project is challenging due to diverse cultures and thought processes. These differences in preferences often disrupt discussions and decision-making processes. Personality analysis tools, as previously discussed, along with Scrum methodologies, can aid managers and Scrum Masters in better understanding their teams. This understanding helps eliminate confusion, improve knowledge sharing, and facilitate informed decision-making by exchanging meaningful information.

Additionally, to foster employee communication, managers can utilize the Kanban dashboard with Jira tools to help employees limit their work in progress, thereby enhancing their productivity and efficiency. Through Jira's Kanban dashboard, managers can easily track project progress and day-to-day updates on employee work. This accessibility enables managers to make informed decisions based on Kanban dashboard information, even in emergencies, eliminating the need to depend solely on employees. It may allow them to address disruptions, reducing employee redundancies and repetitive tasks proactively. Consequently, this streamlines processes and further improves employee job performance.

Managers can consider evaluations based on effective communication, knowledge sharing, and decision quality metrics to comprehensively assess job performance. Strategically integrating digital tools into workflows may help managers align with organizational processes, fostering employee knowledge sharing and effective decision-making, which results in improved job performance.

Limitations and Future Research

The research focused solely on pan India IT sector employees, limiting the generalizability of findings to other industries or countries. Future studies could encompass diverse sectors to obtain more intricate intrigues of the impact of digital technologies on various work environments. The study did not incorporate control variables, which could have provided a deeper understanding of the nuanced influences of other factors on communication, personality, and job performance in a digitalized workplace. Future research should consider incorporating control variables to ascertain the specific impact of digital technologies. Qualitative methods like focus group discussions or in-depth interviews could provide richer insights.

Future studies can delve deeper into identifying specific digital tools or platforms that distinctly influence communication patterns and the behaviours of extroverted and introverted personality types. Understanding the differential impact of technologies on varying personality traits could offer valuable insights for organizational strategies. Research can explore methodologies or assessment tools to identify employees with specific communication styles or personality traits suitable for digital technology-driven environments. This could assist organizations in better matching employees to roles that leverage their strengths, fostering a conducive and efficient workplace environment. By addressing these drawbacks and studying these avenues for future research, organizations can gain a better understanding of the influence of digital technologies, refine their strategies for leveraging these tools effectively, and facilitate an environment that nurtures employee strengths in a digitalized workspace.

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Received: 05-Sep-2024, Manuscript No. AMSJ-24-15212; Editor assigned: 06-Sep-2024, PreQC No. AMSJ-24-15212(PQ); Reviewed: 26-Sep-2024, QC No. AMSJ-24-15212; Revised: 06-Oct-2024, Manuscript No. AMSJ-24-15212(R); Published: 12-Nov-2024