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Extant research on workplace ostracism has investigated a victimization perspective to understand ostracism at the cost of examining the perpetrator-centric view of ostracism. This study aims to draw on the self-categorization theory and the social exchange theory to investigate the harmful effects of workplace romance in cultivating workplace ostracism from the perspective of perpetrator to combat concerns for victim blaming. This study further proposes that workplace ostracism triggered by workplace romance provokes interpersonal conflict. Besides, this study investigates the moderating role of prosocial behavior in the underlying linkages.

This study uses a multisource, time-lagged research design to collect data from employees working in the service sector organizations in Pakistan. This study analyzes 367 responses using SmartPLS (v 4.0).

The findings of this study reveal that workplace romance elicits workplace ostracism, which, in turn, fosters interpersonal conflict among coworkers. In addition, this study finds that ingroup prosocial behavior strengthens the associations between workplace romance and workplace ostracism, and workplace romance and interpersonal conflict, mediated by workplace ostracism such that the associations are more potent at higher levels of ingroup prosocial behavior and vice versa.

To the best of the authors’ knowledge, this is the first study that examines workplace romance as the perpetrator-centric antecedent of workplace ostracism, and ingroup prosocial behavior in exaggerating the outgroup ostracism and interpersonal conflict.

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.

This study investigated the internal factors that influence the adoption of cryptocurrencies for remittance transactions in the United Arab Emirates (UAE) by examining the relationships between behavioural intention (BI) and perceived risk (PR), as well as the mediating effect of consumer innovation (CI).

The authors developed a structural model using scales from the literature. The authors distributed an online questionnaire, evaluated by five cryptocurrency experts, using a snowball approach and collected 270 responses.

The results revealed that CI mediates the relationship between PR and BI. Also, CI enhances intentions to use cryptocurrencies for remittance transactions. However, PR has a negative impact on BI.

This research adds to the body of knowledge by examining the acceptance 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. This article focusses on the mediating impact of CI on intentions to employ cryptocurrency instruments for international money transfers.

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

This research offers novel insights into CI as a significant predictor of bitcoin product uptake in the remittance business.

The current study focuses on the relationship between total quality management (TQM) and sustainable performance (SP) and examines how TQM practices can facilitate firms' achievement of sustainable performance. Knowledge management (KM), with its four dimensions, i.e. knowledge creation (KCR), knowledge acquisition (KAC), knowledge sharing (KSH) and knowledge application (KAP), is also an essential factor for organizations. Therefore, this study also focuses on the mediating role of KM in the relationship between TQM and sustainable performance.

This study used a survey method to collect data from the managers of 485 manufacturing SMEs working in five major industrial cities in Pakistan. Collected data were analyzed through PLS-SEM with the help of smart-PLS.

The study's findings reveal that TQM practices positively influence the environmental and economic sustainability of the firm. At the same time, there is no evidence that TQM practices positively affect the social sustainability of the firm. Results further elaborate that TQM practices significantly affect all four dimensions of KM. Moreover, KM positively affects the two dimensions of SP, i.e. economic and social sustainability, but surprisingly, the impact of KM on environmental sustainability is not found. Finally, results indicate the significant mediating role of KM between TQM and SP.

This study contributes to bridging research gaps in the literature and advances how TQM, directly and indirectly, helps firms improve sustainable performance via the mediating role of KM.

Research has shown that business model innovation can facilitate most ventures to innovate and remain competitive, yet there has been limited work on how digital leadership capabilities influence business model innovation. Building on the dynamic capabilities view, we address this gap by linking digital leadership capabilities with business model innovation via managerial decision-making through provision of grants received by new ventures.

The study is cross-sectional research. Data have been collected utilizing purposive sampling from 313 founding members of new ventures in high-velocity markets, i.e. from Pakistan. SPSS has been used to conduct the moderated mediation analysis.

Digital leadership capabilities foster the business model innovation of the new ventures because they enable new ventures to capitalize on digital technologies and create new ways of generating value for the customers and themselves. Moreover, managerial decision-making mediates digital leadership capabilities and business model innovation relationship, whereas, grants moderate the indirect positive effect of digital leadership capabilities on business model innovation via managerial decision-making. The study generates initial evidence on the impact of digital leadership capabilities on business model innovation via managerial decision-making for new ventures. We advance knowledge on new ventures’ business model innovation by deep-diving into dynamic capabilities view and emphasizing digital leadership capabilities as a significant driver for business model innovation.

With the help of dynamic capabilities theory, this study analyzes how new ventures make use of digital leadership capabilities to promote business model innovation.

Recently, reverse logistics (RL) has become more prominent due to growing environmental concerns, social responsibility, competitive advantages and high efficiency by customers because of expansion of product selection and shorter product life cycle. However, effective implementation of RL results in some direct advantages, the most important of which is winning customer satisfaction that is vital to a firm's success. Therefore, paying attention to customer feedback in supply chain (SC) and logistics processes has recently increased, so manufacturers have decided to transform their RL into customer-centric RL. Hence, this paper aims to identify the features of a mobile phone which affect consumers’ purchasing behavior and to analyze the causality and prominence relations among them that can help decision-makers, policy planners and managers of organizations to develop a framework for customer-centric RL. These features are studied based on analysis of product review sites. This paper's special focus is on social media (SM) data (Twitter) in an attempt to help the decision-making process in RL through a big data analysis approach.

This paper deals with identifying mobile phone features that affect consumer's mobile phone purchasing decisions. Using the DEMATEL approach and using experts' insights, a cause and effect relationship diagram was generated through which the effect of features was analyzed.

Eighteen features were categorized in terms of cause and effect, and the interrelationships of features were also analyzed. The threshold value is calculated as 0.023, and the values lower than that were eliminated to obtain the digraph. F6 (camera), F13 (price) and F5 (chip) are the most prominent features based on their prominent score. It was also found that the F5 (chip) has the highest driving power (1.228) and acts as a causal feature to influence other features.

The focus of this article is on SM data (Twitter), so that experts can understand the interaction between mobile phone features that affect consumer's decision on mobile phone purchasing by using the results. This study investigates the degree of influence of features on each other and categorizes the features into cause and effect groups. This study is also intended to help organizational decision-makers move toward a reverse customer SC.