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Drawing on institutional theory, this study investigates the role of individual cultural values on the adoption of socially sustainable supply chain management (socially SSCM) for Chinese suppliers facing the normative institutional pressures of guanxi (interpersonal relationships).

Using empirical data collected in three waves from 205 Chinese manufacturers supplying international markets, the proposed theoretical model is tested through partial least squares structural equation modeling (PLS-SEM).

The results indicate that guanxi has a positive impact on socially SSCM, and this positive effect is strengthened when the individual cultural values of the supplier's representative embody high collectivism and low uncertainty avoidance.

This study highlights the leading role of guanxi in improving socially SSCM practices due to its normative institutional force. In addition, the findings suggest that future studies should consider individual differences in supply chain partners, which may lead to distinct reactions when facing normative institutional pressures.

This study suggests international buyers should adopt guanxi management with their Chinese suppliers to encourage them to adopt socially SSCM. In addition, managers should note that the guanxi strategy is more effective when the supplier's representative collectivism is high and uncertainty avoidance is low.

This study contributes to socially SSCM research in emerging economies by unveiling the role of guanxi as a key driver of socially SSCM in the Chinese market and providing empirical evidence of the moderating effect of individual culture on the guanxi normative institutionalization process.

The agricultural supply chain is susceptible to disruptive geopolitical events. Therefore, agri-food firms must devise robust resilience strategies to hasten recovery and mitigate global food security effects. Hence, the central aim of this paper is to investigate how supply chains could leverage digital technologies to design resilience strategies to manage uncertainty stemming from the external environment disrupted by a geopolitical event. The context of the study is the African agri-food supply chain during the Russian invasion of Ukraine.

The authors employ strategic contingency and dynamic capabilities theory arguments to explore the scenario and conditions under which African agri-food firms could leverage digital technologies to formulate contingency strategies and devise mitigation countermeasures. Then, the authors used a multi-case-study analysis of 14 African firms of different sizes and tiers within three main agri-food sectors (i.e. livestock farming, food-crop and fisheries-aquaculture) to explore, interpret and present data and their findings.

Downstream firms (wholesalers and retailers) of the African agri-food supply chain are found to extensively use digital seizing and transforming capabilities to formulate worst-case assumptions amid geopolitical disruption, followed by proactive mitigation actions. These capabilities are mainly supported by advanced technologies such as blockchain and additive manufacturing. On the other hand, smaller upstream partners (SMEs, cooperatives and smallholders) are found to leverage less advanced technologies, such as mobile apps and cloud-based data analytics, to develop sensing capabilities necessary to formulate a “wait-and-see” strategy, allowing them to reduce perceptions of heightened supply chain uncertainty and take mainly reactive mitigation strategies. Finally, the authors integrate their findings into a conceptual framework that advances the research agenda on managing supply chain uncertainty in vulnerable areas.

This study is the first that sought to understand the contextual conditions (supply chain characteristics and firm characteristics) under which companies in the African agri-food supply chain could leverage digital technologies to manage uncertainty. The study advances contingency and dynamic capability theories by providing a new way of interacting in one specific context. In practice, this study assists managers in developing suitable strategies to manage uncertainty during geopolitical disruptions.

This study aimed at determining factors which affect university lecturers’ adoption of the Moodle platform under the conditions of COVID-19. In considering the condition of the COVID-19 pandemic, the unified theory of acceptance and use of technology (UTAUT) model was applied and extended by adding two additional variables of learning demand and time pressure to assess their influence on Moodle platform adoption.

Data were obtained from the 226 participants through an online structured questionnaire. The covariance-based approach of structural equation modeling was used to examine the proposed model. The structural model was tested using the maximum likelihood method of analysis of a moment structures to analyze the study’s hypotheses.

Results suggest that performance expectations have a substantial influence on behavioral intent. The effort expectancy, social effect and facilitative factors have no effects on behavioral intentions. Facilitating conditions directly and significantly affect the actual use of Moodle. The results also reveal that learning demands, which is a salient predictor of perceived time pressure, in turn directly and significantly affects the actual use of Moodle. Finally, the behavioral intention has a strong influence on Moodle’s actual usage.

Although the UTAUT 2 model is considered to be a new and updated version of UTAUT, it has not been used since newly added variables, namely, price, habit and hedonic motivations, are less related to the context and to avoid respondents’ paradox. Moreover, using the Moodle platform in the researched context is compulsory for both students and instructors. Discussion, insights, limitations and recommendations for future studies are suggested.

This study aimed to evaluate the factors that determine an individual's decision to adopt human resources (HR) analytics. This study attempts to extend Unified Theory of Acceptance and Use of Technology - 2 (UTAUT2) to identify the lag rate in adoption.

Responses were obtained from 387 HR employees of the Banking Financial Services and Insurance (BFSI) sector in metropolitan cities of India through nonprobabilistic purposive sampling. The analysis was performed through hierarchical regression, structural equation modeling and moderation of resistance to change.

The results suggest that performance expectancy, hedonic motivation and data availability are endorsed by proponents of the intention to adopt HR analytics. In contrast, effort expectancy, social influence, quantitative self-efficacy and habits did not influence behavioral intention (BI). Additionally, the actual use behavior (UB) of HR analytics was determined by BI and facilitating conditions. Furthermore, the moderating effect of resistance to change is explored.

This study makes a significant contribution to the literature on the adoption of HR analytics. By appropriately concentrating on the adoption intention of HR analytics, organizations can intensify healthy employee relationships, thus encouraging the actual usage of HR analytics.

This study formulates a conceptual framework for the adoption of HR analytics that can be used by top management to formulate strategies for the implementation of HR analytics. Moreover, this study aimed to expand UTAUT2, emphasizing the concept of data availability and quantitative self-efficacy and examining the moderating role of resistance to change in the relationship between BI and UB.

HR analytics is a process for systematic computational analysis of data or statistics. It discovers, interprets and communicates significant patterns in data to enable evidence-based HR research and uses analytical insights to help organizations achieve their strategic objectives. However, its adoption and utilization among HR professionals remain a subject of concern. This study aims to determine the reasons that facilitate or inhibit the acceptance of HR analytics among HR professionals in the banking, financial services and insurance (BFSI) sector.

A sample of 387 HR professionals in BFSI firms across India was collected through non-probabilistic purposive sampling. Structural equation modeling was applied to analyze the association between predetermined variables. In addition, the predictive relevance of “Data Availability” was analyzed using hierarchical regression.

The results revealed that data availability, hedonic motivation and performance expectancy positively influenced behavioral intention (BI). In contrast, effort expectancy, social influence and habit had an insignificant effect on BI. Also, facilitating conditions (FCs), habit, BI achieved a variance of 60% in HR analytics use. The use behavior of HR analytics was significantly influenced by FCs and BIs.

This study focuses on insights into the elements that influence HR analytics adoption, revealing additional light on success drivers and grey areas for failed adoption.

This research adds to the body of knowledge by identifying factors that hinder the adoption of HR analytics in Indian organizations and signifies the relevance of easy accessibility and availability of data for technology adoption.

The COVID-19 crisis has sped up digital transformation and technologies by several years. Customers have dramatically shifted to online channels, and businesses have quickly responded by offering additional canals for online shopping and payment. Customers have also been exhibiting greater preferences for contactless payments, and mobile banking has therefore become a norm in both developed and developing countries. This study aims to understand the antecedents of mobile banking actual usage in an early adoption stage setting (i.e. Morocco) through a comprehensive conceptual model combining the unified theory of acceptance and use of technology, the DeLone and McLean IS success model and additional constructs extracted from extent literature. The moderating effects of age, gender and education are also examined and analyzed using multigroup analysis.

Based on data collected from 616 Moroccan users, the authors empirically tested the proposed conceptual model using structural equation modeling.

First, consumer M-banking actual usage has a significant effect on customer satisfaction and attitudinal loyalty; at the same time, attitudinal loyalty was significantly influenced by customer satisfaction. Second, while M-banking actual usage was significantly influenced by effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, habit, service quality, trust, attitude and perceived security, the results show no significant impact of system quality and information quality. Third, the relationship between M-banking actual usage and its antecedents was significantly moderated by age, gender and education.

The findings help bank practitioners to understand the importance of meeting customers’ needs and expectations as a prerequisite in enhancing actual usage, satisfaction and attitudinal loyalty. More importantly, the authors emphasize the need for demographically oriented strategies to target different demographic segments of customers.

The study bridges a gap in M-banking literature by offering a thorough understanding of consumers’ mobile banking use during the pandemic. The findings provide evidence of the applicability of the conceptual model proposed in this research. Furthermore, the reflection of the moderating effects of gender, age and education emphasizes the mobile banking usage disparities among dissimilar demographic segments.

Financial inclusion provides access to financial infrastructure, facilitating money transfers. Therefore, blockchain and cryptocurrencies might boost worldwide financial acceptance. However, the UAE has one of the lowest cryptocurrency adoption rates. This study explores the UAE customer adoption and use of cryptocurrencies.

Using a scale, the authors created a structural model and obtained 270 responses from a snowball-distributed online questionnaire, assessed by five cryptocurrency specialists.

Performance expectations (PE), price value (PV), Hedonic motivation (HM) and consumer innovativeness (CI) were the most significant predictors of behavioural intention (BI). Surprisingly, BI is not a reliable indication of actual consumption. Facilitating conditions (FC) are the most accurate predictor of cryptocurrency usage (CU), indicating that adoption might be increased by providing the necessary structures and processes to lead users.

This research adds to the body of knowledge by examining the adoption and implementation of cryptocurrencies in the UAE and by developing and evaluating new constructs based on current notions. The study also contributes to the current understanding of cryptocurrencies and blockchain adoption.

The conclusions of the research advise marketers on how to boost the commercialisation of cryptocurrencies in the UAE market and may pave the way for other studies to assist impending developments in the UAE cryptocurrency industry.

This research offers novel insights into significant predictors of cryptocurrency product uptake in the financial and banking business.

The research examines how behavioral intentions, as a higher-order construct, indirectly affect financial inclusion through service trust, usage behavior and financial literacy in mobile money adoption.

Following the positivist research philosophy, a cross-sectional study design was used to collect data through questionnaires comprised of scales adapted from prior studies. With a usable sample size of 340 respondents, this study employs partial least squares structural equation modeling to assess the model.

The study revealed the significant indirect role of behavioral intention on financial inclusion through use behavior, behavioral intentions on use behavior through service trust, and use behavior on financial inclusion through financial literacy. The role of behavioral intentions on financial inclusion through serial mediation of service trust, use behavior and financial literacy was also found to be significant.

This study's novelty resides in examining the indirect relationship between behavioral intentions and financial inclusion, specifically via the serial mediation of service trust, use behavior and financial literacy.

Open banking, with its promise to revolutionise electronic transactions through open application programming interfaces (APIs), aims to bridge the gap between banks and non-banks, enhancing lending, payments, investments and funds distribution. However, does this bold innovation truly resonate with consumers? This study delves into consumer intentions to adopt open banking in Indonesia by leveraging the technology readiness model, scrutinising its antecedents and moderating factors, and identifying the key attributes that users anticipate.

Through quantitative and qualitative approaches, this study answers the following questions: (1) Are financial service users ready to use open banking/open API applications? (2) What are the key attributes that consumer expects of open banking/open API? First, the authors developed a structural model based on the technology readiness model, distributed the questionnaire in eight major cities in Indonesia, analysed it using PLS-SEM and utilised a machine learning approach to unpack the main attributes expected from open banking.

This study’s findings indicate that customers are generally prepared to embrace open banking innovations. Nonetheless, to enhance public acceptance, certain factors should be emphasised, including organisational support, user-friendly technology, a comprehensive range of features, consumer financial literacy and banks' readiness to adopt open banking. In contrast to prior research, this study reveals that loyalty to traditional banking positively moderates the connection between customer value and the intention to utilise open banking. Additionally, the authors did not observe a significant moderating effect of financial literacy on the relationship between perceived customer value and the intention to use open banking.

To the best of the authors’ knowledge, this study is one of the few that comprehensively analyses the consumers' readiness for open banking in developing contexts. This study is expected to produce a theoretical contribution as well as effective and optimal policies for the financial services sector.