Search results

This study is based on the heuristic-systematic model (HSM) to dynamically examine the effect of review variance on sales and the boundary conditions that mitigate this effect.

Based on the theoretical domain of HSM, a conceptual model is proposed that analyzes the nonlinear relationship between review variance and sales and the interaction and motivation factors that moderate these relationships. Review data from websites targeting the film industry in the USA and South Korea (Korea) were collected to empirically analyze the authors' hypothesis, and panel regression analysis was used for confirmation.

Moderated by interactive and motivational factors, review variance exhibits an inverse-U-shaped relationship with review variance. Specifically, as an interaction factor, review valence and owned social media (OSM) resulted in positive interaction effects, and as a motivation factor, the number of alternatives exhibited a positive interaction effect with review variance. The effect of review variance was less pronounced in the USA than in Korea.

The study outcomes reveal a nonlinear relationship between review variance and sales, thus supporting the contradictory findings of previous studies. This study contributes to the literature by using the HSM as a theoretical framework to verify various HSM mechanisms using online review data. This exploratory study also contributes to the international marketing literature by showing that the effects of review variance vary across cultures.

Pragmatism is very relevant to workplace management and performance measurement, yet in the accounting literature, it is a term used loosely and in a colloquial manner. By drawing on a framework based on classical pragmatism, this study aims to examine how a pragmatic perspective is discernible in the form and use of management control (MC) practices.

This study collects data using a case study of a firm in the green energy construction sector.

Building on the analytical framework, this study provides evidence that a pragmatic perspective is discernible in both form and use of MC practices, through a clear focus on targets rather than variance analysis, the presence of mutable local MC practices characterised by interaction and problem-solving and the absence of other common MC practices with no clear links to ends-in-view. This study also provides evidence of the potential limitations of a pragmatic perspective including myopia and an exacerbation of the inherent bias in organisations towards exploitation.

This research brings analytical clarity to the study of pragmatism in the accounting literature and insights into how a pragmatic perspective is discernible in the form and use of MC practices. Further, the study shows the potential limitations of a pragmatic perspective for management.

This paper aims to examine the extent to which performance indicators (PIs) reported by New Zealand (NZ) higher education institutions (HEIs) correspond with accounting standards and guidance and the effects issuance of principles-based authoritative guidance and early adoption of Public Benefit Entity Financial Reporting Standard 48 (PBE FRS 48) have on the PIs disclosed.

Using a content analysis index derived from accounting standards and guidance, we conduct a longitudinal assessment of the 2016 and 2019 statements of service performance published by 22 NZ HEIs.

The PIs reported extend beyond the service performance elements proposed by standard-setters. Despite few indicators on intermediate and broader outcomes, the measures disclosed by HEIs are reflective of their role in the NZ economy and the national Tertiary Education Strategy. The results show that principles-based authoritative guidance and early adoption of PBE FRS 48 influence the focus and type of measures disclosed, while there is no evidence of improvements in the reporting of impacts, outcomes and information useful for performance evaluation.

This paper provides timely insights for standard-setters and regulators on the influence principles-based accounting standards and guidance have on non-financial reporting practices.

This study contributes to the scant literature on HEIs’ service performance reporting. It presents a model for conceptualising HEIs’ PIs that can be used as a basis for future research on non-financial reporting. It also reflects on the tension between accountability and “accountingisation”, suggesting that, although the PIs reported support formal accountability, they do not communicate whether HEIs’ activities and outputs meet their social purpose.

Drawing on the conservation of resources (COR) theory, this study aims to assess the moderating effect of the psychological contract (PC) type (relational, transactional and balanced) on the relationship between psychological contract breach (PCB) and organizational citizenship behaviours (OCBs).

The authors administered a survey to a sample of 159 nurses working in a large public hospital. To analyse the survey data, the authors used partial least squares with SmartPLS v.3.3, a variance-based structural equation modelling technique that combines principal component analysis, path analysis and regression analysis.

This study shows that nurses counteract the loss of resources following a PCB by investing more in stronger interpersonal relationships with co-workers and patients as a way to recuperate from resource loss and gain social resources. In addition, the moderating effect of the PC type reinforces the relationship between a PCB and OCB in a way that relational and balanced PC types support OCB-I positively but negatively OCB-O. Furthermore, the transactional PC does not reinforce negatively the link between PCB and OCB-I, and the negative interacting effect on the PCB and OCB-O link is only partially supported.

The study findings are grounded on a cross-sectional research design and a convenience sampling strategy.

The results highlight the relevance of human resources management practices centred on employee involvement and participatory supervision styles for ensuring OCB display at the workplace.

The results add new evidence to COR theory by highlighting the importance of social resources as a mitigator in the relationship between nurses’ PCB and OCB towards co-workers and patients (OCB-I). Hence, the OCB-I display will vary in function of the target and the moderating effect of PC type (relational, balanced or transactional).

Drawing on social exchange theory (SET) and proactive motivation model, this study aims to examine the relationship between workplace dignity and employees’ tacit knowledge sharing (TKS) and assess the mediating role of psychological safety and organizational identification in this relationship.

Data are collected in the three waves from 307 first-line supervisors and professionals of high- and medium-high-tech manufacturing organizations of Pakistan. Partial least squares structural equation modelling technique is applied using SmartPLS 4 software to test hypothesized relationships.

Results reveal that workplace dignity is directly and positively related to TKS and psychological safety and organizational identification mediate this relationship.

This study highlights the importance of workplace dignity as a vital determinant of TKS. Findings of this research underscore the need for enactment of humanistic and employee-oriented organizational policies and practices that signal workplace dignity which can result in increased psychological safety and enhanced organizational identification leading towards higher TKS.

This research proffers novel understanding of the nexus between an embryonic socio-emotional element of workplace context, namely, workplace dignity and TKS. This study not only advances knowledge management literature from dignity perspective but also contributes to SET and proactive motivation model.

The primary objective of this research is to provide a precise interpretation of the constructed machine learning model and produce definitive summaries that can evaluate the influence of investor sentiment on the overall sales of non-fungible token (NFT) assets. To achieve this objective, the NFT hype index was constructed as well as several approaches of XAI were employed to interpret Black Box models and assess the magnitude and direction of the impact of the features used.

The research paper involved the construction of a sentiment index termed the NFT hype index, which aims to measure the influence of market actors within the NFT industry. This index was created by analyzing written content posted by 62 high-profile individuals and opinion leaders on the social media platform Twitter. The authors collected posts from the Twitter accounts that were afterward classified by tonality with a help of natural language processing model VADER. Then the machine learning methods and XAI approaches (feature importance, permutation importance and SHAP) were applied to explain the obtained results.

The built index was subjected to rigorous analysis using the gradient boosting regressor model and explainable AI techniques, which confirmed its significant explanatory power. Remarkably, the NFT hype index exhibited a higher degree of predictive accuracy compared to the well-known sentiment indices.

The NFT hype index, constructed from Twitter textual data, functions as an innovative, sentiment-based indicator for investment decision-making in the NFT market. It offers investors unique insights into the market sentiment that can be used alongside conventional financial analysis techniques to enhance risk management, portfolio optimization and overall investment outcomes within the rapidly evolving NFT ecosystem. Thus, the index plays a crucial role in facilitating well-informed, data-driven investment decisions and ensuring a competitive edge in the digital assets market.

The authors developed a novel index of investor interest for NFT assets (NFT hype index) based on text messages posted by market influencers and compared it to conventional sentiment indices in terms of their explanatory power. With the application of explainable AI, it was shown that sentiment indices may perform as significant predictors for NFT sales and that the NFT hype index works best among all sentiment indices considered.

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

In developing countries, how risk management technologies influence management accounting and control (MAC) practices is under-researched. By drawing on insights from institutional studies, this study aims to examine the multiple institutional pressures surrounding an entity and influencing its risk-based management control (RBC) system – that is, how RBC appears in an emerging market attributed to institutional multiplicity.

The authors used qualitative case study research methods to collect empirical evidence from a privately owned Egyptian insurance company.

The authors observed that in the transformation to risk-based controls, especially in socio-political settings such as Egypt, changes in MAC systems were consistent with the shifts in the institutional context. Along with changes in the institutional environment, the case company sought to configure its MAC system to be more risk-based to achieve its strategic goals effectively and maintain its sustainability.

This research provides a fuller view of risk-based management controls based on the social, professional and political perspectives central to the examined institutional environment. Moreover, unlike early studies that reported resistance to RBC, this case reveals the institutional dynamics contributing to the successful implementation of RBC in an emerging market.

The negative influence of gamification on online communities has received little attention in the available literature. The study examines the adverse effects of gamification during engaging in online communities.

Gap-spotting methods were used to develop the research questions, followed by model development using the social exchange and social-network theories. Data were collected from 429 samples. The study applied partial least squares structural equation modeling to test the research hypotheses followed by ANN application.

The study identified five factors related to gamification that have a significant adverse effect on the mental and emotional well-being of the users. Furthermore, the results of PLS-SEM were then compared through an artificial neural network (ANN) analytic process, revealing consistency for the model. This research presents a theoretical contribution by providing critical insights into online gamers' mental and emotional health. It implies that gamification can even bring mental and emotional disturbance. The resulting situation might lead to undesirable social consequences.

The result highlights the managerial and social relevance from the perspective of a developing country. As respondents are becoming more engrossed in online gaming, managers and decision-makers need to take preventive measures to overcome the dark side of online gaming.

The present study shows that the dark side of gamification has some adverse effects on human mental and emotional health. The study's findings can be used to improve gamification strategies while engaging online communities.

Battery electric vehicles (BEVs) are living up to their claims as consumers choose them more frequently. The increasing demand for sustainable vehicles translates into the global need for specific components, materials, and infrastructures and drives the regulatory frameworks in each country. While BEVs offer environmental benefits and global business opportunities, the technology has not yet gained mainstream acceptance. Thus, this work aims to investigate the characteristics of BEV users and their role in the diffusion of products to larger segments, as this may vary from country to country. For this purpose, a survey based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) (Venkatesh et al., 2012) framework and structural equation modeling (SmartPLS) was adopted. The results indicated that, except for the constructs of effort expectancy (EE) and social influence (SI), the predictors in the model performed well in this context. Current users are satisfied with their vehicles and are supportive of BEVs in the future. The analysis also revealed that in addition to the availability of financial resources, early adopters are attracted by new technologies in a way that leads them to make decisions outside of the traditional influence of the other members of society. It is suggested to leverage the perceived benefits of status, differentiation, or uniqueness motives, to appeal to those seeking to appear trendy and tech-savvy in society. Companies and policymakers should acknowledge the peculiarities of early customers in their communication strategies to reach a wider audience around the globe and encourage the adoption of BEV technology.