Search results

The use of innovative technologies by firm employees is a key factor in ensuring the competitiveness of firms. However, researchers and practitioners have been concerned about the willingness of technology end users to use innovative technologies. This study, therefore, aims to determine the factors affecting the intention to use marketing analytics technology.

This study surveyed 213 firm employees. The quantitative data collected was analysed using partial least squares structural equation modelling.

The results reveal that performance expectancy, facilitating conditions, attitudes and perceived trust have a positive and significant effect on intentions to use marketing analytics. Effort expectancy, social influence and personal innovativeness in information technology were found not to predict intentions to use marketing analytics.

This study has practical implications for firms seeking to enhance the use of marketing analytics technology in developing countries.

This study contributes to the use of UTAUT, perceived trust, personal innovativeness and user attitude in predicting the intentions to use marketing analytics technology.

This study aims to investigate the effect of organizational ambidexterity (OA) and organizational green culture (OGC) on corporate sustainability (CS) while incorporating the mediating role of green innovation (GI) to provide a detailed insight into CS. The study also presents a research framework based on the Organizational Ambidexterity theory and Natural Resource-based view to explain the factors contributing to CS.

Using stratified sampling, the study collected data through survey-based empirical research from 307 textile companies registered with the Securities and Exchange Commission of Pakistan (SECP) or the All-Pakistan Textile Mills Association (APTMA). The collected data were analysed using path analysis, mediation analysis and moderation analysis through smart PLS-SEM version 4.0 to assess the composition and causal association of factors.

The study found a significant relationship between OA and OGC with CS. Furthermore, the study revealed that green innovation partially mediates the relationship between OGC and CS. The proposed research framework can be valuable for promoting and recommending actions to enhance CS.

The study on CS in the textile sector of Pakistan has limitations such as a narrow focus, cross-sectional design and reliance on self-reported data. Future research should explore additional factors, conduct longitudinal research, investigate contextual factors, scrutinize specific green innovation practices and broaden the scope of the study to include SMEs and other textile organizations.

The research framework can help senior executives to foster CS by promoting OGC, OA and GI. Practitioners and academicians can also utilize or further investigate the proposed framework for validation and to foster CS.

This study fills gaps in the existing literature by investigating the mediating effect of GI between OGC and CS. The proposed research framework provides a comprehensive understanding of the factors contributing to CS based on the Organizational Ambidexterity theory and Natural Resource-based view.

This study investigates the consequences of the key audit matter (KAM) disclosure requirement by considering two salient audit proxies: audit fees and audit report lag. This investigation is relevant because most auditors worldwide are required to expand their audit report including discussion on key matters faced in the audit engagement. However, the emerging literature on the implications of KAM is inconclusive.

Using a distinctive dataset of 601 year-observations for firms listed on the Omani capital market over 2012–2019, this study employs pooled panel data regression with robust standard error.

Results indicate that auditors increased their fees considerably during the period of KAM but substantially shortened audit report lag. Conversely, using the KAM period as a sample, the authors find marginal or insignificant evidence for the effect of the number of KAM on both proxies. In additional analyses, this study shows that entity-level risk KAM is associated with higher fees and shorter audit report lag, while KAM related to account-level risk does not have the same effect. Interestingly, it is observed that KAM disclosure is strongly associated with higher fees and high-quality audit even when the auditors issue their report in a shorter time.

This study contributes to the limited research examining the consequences of KAM in emerging markets. It is also the first to show that KAM is associated with shorter audit report lag.

The purpose of this study was to investigate the connection between green human resource management (GHRM) and corporate social responsibility (CSR). In addition, this study also investigates how the impact of GHRM varies depending on the extent of transformational leadership.

Adopting a quantitative approach, the sample consists of 376 employees who hold leadership positions in the academic body and those who work in human resources units at universities who won the Web Metric Award.

Results have shown that all GHRM practices were found to have a significant and positive effect on CSR. In addition, the findings revealed that transformational leadership positively moderates the relationship between GHRM and CSR.

The findings of this study contribute to the existing body of knowledge by providing empirical evidence of the positive relationship between GHRM practices, transformational leadership and CSR performance. In addition, the study highlights the moderating influence of transformational leadership on the relationship between GHRM and CSR, suggesting that transformational leadership can increase the efficacy of GHRM practices in promoting CSR outcomes.

Social innovation is a nascent field. Within research on social innovation, the context of higher education has largely been ignored. To better understand social innovation, it is important to explore factors that facilitate social innovation in universities’ context. There is little research on enablers of social innovation in universities and the impacts of social innovation. Therefore, the purpose of this study is to understand the enablers of social innovation in the Saudi Arabian context. Moreover, the impacts of social innovation projects are also explored.

A qualitative approach was used to carry out this study. Data were collected through semistructured interviews, and content analysis was performed.

Data revealed that institutional commitment, mission, active collaborations, curriculum, support, training, community university engagement offices, university social impact offices and reward and evaluation were among critical enablers. The impact of social innovation in terms of social, institutional, economic and community specific was also reported.

Research on the enablers and outcomes of social innovation in the higher education context is limited. This study adds to the innovation literature by investigating what processes and factors (enablers) can help universities to engage in social innovation initiatives and what are the outcomes (impact) of engaging in social innovation. Findings of the study have important policy implications.

The study aims to explore the effectiveness of performance-oriented practices like high-performance work practices (HPWPs) in higher education (HE), given its explicit focus on performance these days.

The study uses hierarchical linear modeling using statistical package for social sciences (SPSS 22.0) to test the hypotheses. An intertwined framework of the ability–motivation–opportunity (AMO) model and the job demand-resources (JD-R) model was proposed. The study considered strategic hiring, recognition and participatory decision-making as ability, motivation and opportunity-enhancing practices respectively. Further, the study addressed the impact of institutional level moderators, like administrative workload (AWL) and support staff (SS).

The findings based on the responses of 385 faculties and 443 students from 36 Indian institutes, indicated that HPWPs enhanced the education performance (EP) of HE institutes. Further, results revealed that both AWL and SS had differential effects on the relationship between HPWPs and EP. Contrary to authors’ expectations, SS showed a negative effect of the relationship between HPWPs and EP.

The increased AWL was debilitating the beneficial effects HPWPs. The negative interaction effect of SS sheds light on the hidden issues surrounding SS in HE institutes. Based on findings, the study offered important theoretical and practical implications.

To the best of authors’ knowledge, the impact of innovative human resource (HR) practices in academia remains relatively under-researched, and the current study is an attempt to fill this void.

Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hinder smooth implementation of big data technology in project teams.

This study uses constructs from conflict theory, and team power relations to develop an explanatory framework. The study proceeded to formulate theoretical hypotheses from task-conflict, process-conflict, relationship and team power conflict. The hypotheses were tested using Partial Least Square Structural Equation Model (PLS-SEM) to understand key preventive measures that can encourage conflict prevention in project teams when implementing big data technology.

Results from the structural model validated six out of seven theoretical hypotheses and identified Relationship Conflict Prevention as the most important factor for promoting smooth implementation of Big Data Analytics technology in project teams. This is followed by power-conflict prevention, prevention of task disputes and prevention of Process conflicts respectively. Results also show that relationship and power conflicts interact on the one hand, while task and relationship conflict prevention also interact on the other hand, thus, suggesting the prevention of one of the conflicts could minimise the outbreak of the other.

The study has been conducted within the context of big data adoption in a project-based work environment and the need to prevent innovation-induced conflicts in teams. Similarly, the research participants examined are stakeholders within UK projected-based organisations.

The study urges organisations wishing to embrace big data innovation to evolve a multipronged approach for facilitating smooth implementation through prevention of conflicts among project frontlines. This study urges organisations to anticipate both subtle and overt frictions that can undermine relationships and team dynamics, effective task performance, derail processes and create unhealthy rivalry that undermines cooperation and collaboration in the team.

The study also addresses the uncertainty and disruption that big data technology presents to employees in teams and explore conflict prevention measure which can be used to mitigate such in project teams.

The study proposes a Structural Model for establishing conflict prevention strategies in project teams through a multidimensional framework that combines constructs like team power conflict, process, relationship and task conflicts; to encourage Big Data implementation.