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With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).

The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).

A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.

This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.

This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.

The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.

This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.

Technology is widely recognised to be revolutionising the accounting profession, allowing accountants to focus on professional skills and technical knowledge that deliver value for organisational success. Despite the known benefits, it is reported that accountants are not fully leveraging the potential value of certain technologies. To understand why, this study aims to draw on the technology adoption model (TAM) and investigates accounting professionals’ perceptions towards technology, and how these may influence adoption at work.

The study gathered online survey data from 585 accounting managers from organisations of varying sizes and in different sectors in Australia and parts of Southeast Asia. Qualitative data were thematically analysed, and quantitative data were analysed using both descriptive and multivariate techniques.

The study highlighted the pivotal role of staff perceptions on the importance and ease of using technology on the uptake and successful usage. Findings emphasised important opportunities for organisations to educate accounting staff on the value of technology and optimise their confidence and skills through training and support initiatives, particularly smaller businesses. Marked differences in the orientation towards technology among Australian and Southeast Asian participants illuminate how national work culture and practice can influence technology adoption.

The study makes a practical contribution by advancing the understanding of the relative importance and value of certain technologies in different regions and organisation types in the accounting profession. It extends the theoretical understanding of the role of TAM’s core elements to the accounting context, exploring staff’s notions of perceived usefulness and perceived ease of use from the manager’s perspective.

Faculty play a unique role in universities performing duties along the three fronts of teaching, research and service. While it might be teaching that contributes most to the bottom line of a small university, it is often research by which faculty merit is judged. This study explores the relationships between role ambiguity, role conflict and commitment (affective, normative and continuance) as mediated by job satisfaction among faculty members.

A sample of 133 faculty members at a US-accredited university in Lebanon served as the basis for this study. The faculty members completed a survey covering scales on role ambiguity, role conflict, commitment and job satisfaction in addition to demographic variables.

We find that a decrease in role ambiguity strengthens affective and normative commitment but weakens continuance commitment. Structural equation modeling indicates that job satisfaction partially mediates the relationship between role ambiguity and affective commitment, while not mediating the relationship between role ambiguity and normative and continuance commitments. Similar findings hold for job satisfaction as a mediator in the relationship between role conflict and commitment.

Based on statistical modeling, this work (1) puts forth a revised scale for organizational commitment tailored to academia and (2) provides guidance to higher education institutions in terms of the differential impacts on faculty commitment that stem from reducing role-ambiguity versus role-conflict. Managerial recommendations focus on improving normative and affective commitment through the design of policies to reduce role conflict among faculty.

Within North American institutions of higher education, the sociopolitical construct of whiteness comprises an often implicit set of lessons that are reflected not only in policy and curricula but also in the teaching practices of faculty. Such lessons perpetuate white centricity and supremacy, at enormous costs to those who have been negatively racialized. Therefore, it is critical for white faculty to engage meaningfully with ongoing processes of self-reflection, self-education, and skill development so that they can contribute positively to the interrogation and disruption of whiteness in higher education. This chapter discusses seven processual considerations for white educators who seek to interrogate and disrupt the problem of whiteness in teaching and learning.

The paper aims to explore the relationship between customer mindsets and customer citizenship behavior. This study used the cognitive-affective-behavioral model to examine how customer mindsets relate to customer citizenship behavior. In addition, it investigated the mediating effect of customer brand engagement and moderating role of brand trust.

The study used a self-administered online survey from 412 respondents using cellular mobile operating brands. Partial least square structural equation modeling was used to analyze the collected data.

The results revealed that growth-mindset customers directly and significantly influence customer citizenship behavior. The impact of a fixed mindset on customer citizenship behavior is indirect through customer brand engagement. The moderating findings revealed that the effect of brand trust on the relationship between customer brand engagement and customer citizenship behavior is higher than that between the fixed mindset and customer brand engagement.

The findings provide valuable insights for marketing and brand managers to design marketing campaigns considering different mindsets to generate customer citizenship behavior among customers.

This study provides new avenues in consumer psychology and behavior by unfolding the underlying mechanism through which mindsets lead to customer citizenship behavior, contributing to existing knowledge by extending the cognitive-affective-behavioral model.

Effective customer journey design (ECJD) is considered a key variable in customer experience management and an essential source of brand meaning and pro-brand behavior. Although previous research has confirmed its importance for driving brand attitudes and loyalty, the role of consumer-brand identification as a social identity-based influence in this relationship has not yet been discussed. Drawing on construal level and social identity theories, this paper aims to investigate whether effective journeys and the resulting overall journey experience are equally powerful in driving brand loyalty among customers with different levels of consumer-brand identification.

The present article develops and tests a research model using data from the European and US service sectors (N = 1,454) to investigate how and when ECJD affects service brand loyalty.

Across two cultural contexts, four service industries and 33 service brands, the results reveal that ECJD is a crucial driver of service brand loyalty for customers with low consumer-brand identification. Moreover, the findings show that different aspects of journey effectiveness positively impact the valence of customers’ experience related to those journeys – a process that is ultimately decisive for their brand loyalty.

This study is unique because it generates theoretical and practical knowledge by combining the literature streams of customer journey design, customer experience and branding. Furthermore, this work demonstrates that consumer-brand identification is a critical boundary condition to be considered in the relationship between ECJD and brand loyalty in services.

In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation and the business model revolution. This paper aims to investigate whether and how the application of AI enhances the ESG performance of enterprises.

This study uses panel data from Chinese A-share listed companies spanning the period from 2012 to 2022. Through a multivariate regression analysis, it examines the impact of AI on the ESG performance of enterprises.

The findings suggest that the application of AI in enterprises has a positive impact on ESG performance. Internal control systems within the organization and external information environments act as mediators in the relationship between AI and corporate ESG performance. Furthermore, corporate compliance plays a moderating role in the connection between AI and corporate ESG performance.

This paper underscores the pivotal role played by AI in enhancing corporate ESG performance. It explores the pathways to improving corporate ESG behavior from the perspectives of internal control and information environments. This discussion holds significant implications for advancing the application of AI in enterprises and enhancing their sustainable governance capabilities.

This research paper aims to investigate the critical factors influencing the live commerce industry and their implications for Key Opinion Leaders (KOLs) and brands.

The study comprehensively reviews previous research, develops relevant hypotheses and utilizes personal information from 66 anchors, along with data from 23,000 product links obtained from the backends of live commerce platforms.

The study emphasizes that KOLs with higher traffic significantly influence Gross Merchandise Volume (GMV). Intriguingly, KOLs with lower traffic levels exhibit a more pronounced effect on Return on Investment (ROI), highlighting their significance in driving profitability. Furthermore, the study explores the correlation between KOL hashtags and GMV/ROI and the intricate relationship between product types and KOL hashtags.

The findings significantly enhance the understanding of live shopping behavior and provide valuable insights for business management strategies. Practitioners can leverage this empirical evidence to make informed decisions, utilizing extensive data samples of KOLs and brands.

This research contributes unique insights into the live-streaming commerce industry using backend data from Live Streaming E-commerce platforms. The findings are more accurate based on market data than previous studies that relied on platform reviews or questionnaires. Additionally, this paper investigates the impact of KOLs on the performance of live e-commerce from three perspectives: GMV, ROI and hot-selling products.