Hemlata Gangwar, Mohammad Shameem, Sandeep Patel, Alex Koohang and Anuj Sharma
Generative artificial intelligence (GenAI) can potentially improve supply chain management (SCM) processes across levels and verticals. However, despite its promise, the…
Abstract
Purpose
Generative artificial intelligence (GenAI) can potentially improve supply chain management (SCM) processes across levels and verticals. However, despite its promise, the implementation of GenAI for SCM remains challenging, mainly due to the lack of knowledge regarding its key drivers. To address this gap, this study examines the factors driving GenAI implementation in an SCM environment and how these factors optimize SCM performance.
Design/methodology/approach
A thorough literature review was followed to identify the drivers. The resultant model from the drivers was validated using a quantitative study based on partial least squares structural equation modeling (PLS-SEM) that used responses from 315 expert respondents from the field of SCM.
Findings
The results confirmed the positive effect of performance expectancy, output quality and reliability, organizational innovativeness and management commitment to GenAI usage. Further, they showed that successful GenAI usage improved SCM performance through improved transparency, better decision-making, innovative design, robust development and responsiveness.
Practical implications
This study reports the potential drivers for the contemporary development of GenAI in SCM and highlights an action plan for GenAI’s optimal performance. The findings suggest that by increasing the rate of GenAI implementation, organizations can continuously improve their strategies and practices for better SCM performance.
Originality/value
This study establishes the first step toward empirically testing and validating a theoretical model for GenAI implementation and its effect on SCM performance.
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Manaf Al-Okaily and Aws Al-Okaily
Financial firms are looking for better ways to harness the power of data analytics to improve their decision quality in the financial modeling era. This study aims to explore key…
Abstract
Purpose
Financial firms are looking for better ways to harness the power of data analytics to improve their decision quality in the financial modeling era. This study aims to explore key factors influencing big data analytics-driven financial decision quality which has been given scant attention in the relevant literature.
Design/methodology/approach
The authors empirically examined the interrelations between five factors including technology capability, data capability, information quality, data-driven insights and financial decision quality drawing on quantitative data collected from Jordanian financial firms using a cross-sectional questionnaire survey.
Findings
The SmartPLS analysis outcomes revealed that both technology capability and data capability have a positive and direct influence on information quality and data-driven insights without any direct influence on financial decision quality. The findings also point to the importance and influence of information quality and data-driven insights on high-quality financial decisions.
Originality/value
The study for the first time enriches the knowledge and relevant literature by exploring the critical factors affecting big data-driven financial decision quality in the financial modeling context.
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Jing Xiao, Ping Zeng and Lanlan Niu
Implementing a green strategy to enhance the competitiveness of enterprises is a hot topic in current research. Although most enterprises have formed a green strategy orientation…
Abstract
Purpose
Implementing a green strategy to enhance the competitiveness of enterprises is a hot topic in current research. Although most enterprises have formed a green strategy orientation (GSO), it has not been transformed into green competitiveness (GC). Prior studies have not thoroughly studied the effect and mechanism of GSO on GC. To fill this research gap, based on optimal distinctiveness theory, this paper discusses the mediating role of two kinds of green innovation (GI) in the GSO–GC relationship and the moderating role of big data capability (BDC).
Design/methodology/approach
This study adopts the quantitative research methods of multiple linear regression, Bootstrap and structural equation modeling (SEM). Data were collected through a questionnaire and a random sampling method was used to survey middle and senior managers and professionals in manufacturing enterprises. About 400 questionnaires were distributed, and 342 valid questionnaires were collected.
Findings
The conclusions show that GSO significantly positively affects GI and GC. Still, it turns out that only strategic green innovation (SGI) mediates the GSO–GC relationship. BDC can positively moderate the mediation effect of SGI between GSO and GC, thus supporting the moderated mediation model.
Research limitations/implications
This study used a survey questionnaire from Chinese manufacturing enterprises to collect data, but the sample size was limited. Furthermore, the mediating mechanism by which GSO affects GC requires further exploration. This study directly establishes the GSO–GC relationship based on the optimal distinctiveness theory, making an essential contribution to the literature on GSO and GC. At the same time, this paper uses GI as a bridge to connect the relationship between GSO and GC, enriching the literature on GI. In addition, we consider BDC to be a moderator, expanding the boundaries of the GSO–GC relationship.
Practical implications
This study provides new knowledge and insights for manufacturing enterprises to construct and implement green strategies to achieve GC. More importantly, managers should attach great importance to the critical role of SGI and BDC.
Originality/value
This study understands the importance of GSO, SGI and BDC to GC in theory and practice.
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Shashi, Myriam Ertz, Roberto Cerchione and Vikas Kumar
Despite the numerous benefits of digitalization, many business-to-business (B2B) firms have yet to rely on data-driven decision-making, wavering the decision to adopt digital…
Abstract
Purpose
Despite the numerous benefits of digitalization, many business-to-business (B2B) firms have yet to rely on data-driven decision-making, wavering the decision to adopt digital marketing practices. Topical scholarship is scattered across disciplines, schools of thought and methodological approaches, leading to an inability to suggest better management practices. This study aims to review the extant B2B marketing digitalization literature and addresses these concerns.
Design/methodology/approach
This paper conducted a systematic literature review of 96 high-quality articles extracted from the Web of Science database. Thereafter, this paper carried out descriptive statistical and content analyses of these articles.
Findings
Six primary research streams have been identified, and 16 research propositions have been formulated to comprehensively overview the B2B marketing digitalization landscape. The study delves into the factors and barriers influencing the pace of B2B marketing digitalization, sales lead generation and sales performance. Additionally, it introduces B2B digital value creation frameworks, emphasizing the crucial role of marketing analytics and decision tools in effective B2B marketing. The research also underscores various digitalization strategies aimed at bridging the digitalization gap in B2B companies at both strategic and tactical levels. Finally, the study presents an agenda to stimulate future research on theoretical and managerial topics critical to enriching the field.
Originality/value
This research outlines 16 research propositions that could be further tested to get more detailed insights into the digitalization of B2B marketing. Additionally, practitioners, authorities and researchers in the field may find this review valuable as it provides a comprehensive overview of current research in the domain.
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Zaid Jaradat, Ahmad Mtair AL-Hawamleh and Marwan Altarawneh
The aim of this study is to investigate technological and innovation orientation contribution to the development and sustainability of the industrial sector.
Abstract
Purpose
The aim of this study is to investigate technological and innovation orientation contribution to the development and sustainability of the industrial sector.
Design/methodology/approach
The authors gathered the perspectives of many experts who were aware enough of their company’s technical and innovation orientations to participate in this study to understand how technology and innovation orientations may affect sustainability and development. These people included the company managers, accounting department heads, IT department workers and employees in the innovation department. This was accomplished by distributing a thorough questionnaire intended to gather their perspectives.
Findings
The study’s results highlight the significant positive relationship between technological and innovation orientation. Moreover, the study demonstrates that both technological and innovation orientation were found to positively impact the sustainability and development of the industrial sector.
Practical implications
This study provides practical insights for policymakers, industrial managers and innovation supporters in Jordan. Managers can use these insights to reassess technology adoption and innovation strategies. Additionally, investing in staff skills and technology readiness can boost efficiency, competitiveness and long-term growth.
Originality/value
To the best of the authors’ knowledge, this study is pioneering research to shed light on the connection between technological orientation, innovation orientation and sustainability and development in the industrial sector, providing valuable insights for policymakers and practitioners alike.
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Muhammad Qamar Zia, Muhammad Sufyan Ramish, Syeda Tayyaba Fasih, Muhammad Naveed and Zilong Wang
Based on the conservation of resources (COR) theory, this study seeks to investigate how job embeddedness (JE) and job frustration (JF) as serial mediators linking abusive…
Abstract
Purpose
Based on the conservation of resources (COR) theory, this study seeks to investigate how job embeddedness (JE) and job frustration (JF) as serial mediators linking abusive supervision (AS) to project performance (PP) in the construction industry.
Design/methodology/approach
Data were gathered from 297 respondents working in six organizations involved in large-scale construction projects. The respondents were project managers, field engineers, consultants and civil engineers. Partial least squares structural equation modeling was used for data analysis and hypothesis testing.
Findings
The study findings indicate that JE and JF mediate AS’s impact on PP. The findings further reveal that JE and JF serially mediated the linkage between AS and PP.
Originality/value
This manuscript contributes to the relevant knowledge by investigating the overlooked psychological mechanisms of JE and JF between the linkage of AS to PP. The results of this study hold significant implications for both theoretical research and management practices.
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Jianhua Zhang, Umair Zia, Muhammad Usman Shehzad and Sherani
Nowadays, it is hard to retain a knowledge monopoly since tacit knowledge has become essential for innovation and organizational effectiveness (ORP). This study analyzed the role…
Abstract
Purpose
Nowadays, it is hard to retain a knowledge monopoly since tacit knowledge has become essential for innovation and organizational effectiveness (ORP). This study analyzed the role of product innovation as a mediator in the relationship between the tacit knowledge management process (TKMP) and organizational performance. In addition, two moderating variables were examined: (1) Affective trust (AFT) between the tacit knowledge management process and product innovation relationship and (2) Task efficiency in product innovation and organizational performance (ORP) relationship.
Design/methodology/approach
Around 344 questionnaires were collected from various Chinese regions between February and April 2023 to conduct this study. The regression, mediation and moderation analyses on lower and higher-order data were evaluated using the SmartPLS approach.
Findings
The results validate that product innovation mediates the connection between managing tacit knowledge and the organization’s performance. Affective trust also plays a positive moderating role between tacit knowledge and product innovation. These results provide valuable theoretical and practical insights, substantiating various direct, indirect, mediate, and moderated effects hypotheses.
Research limitations/implications
The scope of the study was restricted to manufacturing companies; however, further research may broaden the model’s scope to include other industries. Furthermore, future research should continue to explore the role of task efficiency in the innovation process and identify strategies for enhancing task efficiency in organizations.
Practical implications
The study establishes the significance of effectively managing tacit knowledge for fostering product innovation. Company managers and leaders can promote employee trust, enhancing innovation capabilities and overall organizational effectiveness.
Originality/value
This study, involving dual moderation, explores the connections between processes of managing tacit knowledge, product innovation and organizational performance. It addresses research gaps, enriching the understanding of managing tacit knowledge, leading to organizational innovation and performance improvements. The study also highlights how affective trust is vital in strengthening the connection between TKMP and product innovation.
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Muhammad Yasir and Kainat Alam
This study aims to examine how employees’ perception of the ethical conduct of their leaders affects their level of green innovation and environmental performance. Therefore, this…
Abstract
Purpose
This study aims to examine how employees’ perception of the ethical conduct of their leaders affects their level of green innovation and environmental performance. Therefore, this study investigated green innovation as a mediator between ethical leadership and environmental performance, specifically within the context of Pakistani restaurants.
Design/methodology/approach
Data was collected from the frontline employees using a convenience sampling method having a sample size of 213 respondents. The hypothesized model was analyzed through structural equation modeling using SmartPLS v3 software.
Findings
This study shows a (i) positive relationship between ethical leadership and environmental performance, (ii) positive association between ethical leadership and green innovation, (iii) positive relationship between green innovation and environmental performance and (iv) green innovation mediates between ethical leadership and environmental performance.
Research limitations/implications
This research suggests that top management of the restaurants needs to focus on exhibiting ethical leadership behavior, thereby fostering green innovation practices that will improve the environmental performance of Pakistani restaurants.
Originality/value
The current study is novel as it investigates the association between ethical leadership, green innovation and environmental performance, specifically within the context of Pakistani restaurants.
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Artificial intelligence (AI) integration in the workplace yields positive outcomes, yet its impact on employees remains incompletely understood. This study aims to examine…
Abstract
Purpose
Artificial intelligence (AI) integration in the workplace yields positive outcomes, yet its impact on employees remains incompletely understood. This study aims to examine employee viewpoints regarding AI and its influence on employee career attitudes, behaviors and skill enhancement. The author examines how employees perceive AI and its impact on their career adaptability within the context of career self-management.
Design/methodology/approach
The researchers conducted hypothesis testing using AMOS; data was collected from 255 software house employees working in Pakistan. This study is time-lagged in nature. Data on AI perception was collected at time 1. After three weeks, data was collected for hypotheses related to mediation, and employees filled out a questionnaire related to career adaptability at time 3 with the interval of three weeks.
Findings
This study indicates a strong correlation between beliefs about AI dominance in the job market and increased career adaptability. The researchers discovered that career insecurity and skill development are pathways that elucidate employees’ perceptions of AI dominating their decisions regarding career adaptability.
Originality/value
This study demonstrates that AI perception has the potential to influence employees, motivating them to enhance their abilities and pursue adaptable career trajectories. The study indicates that employees’ unfavorable perceptions of AI can result in behaviors associated with career adaptability.