Search results

Hedonic shopping is a growing phenomenon designed to enhance gamers’ virtual content shopping experience with increasing economic significance, yet limited attention has been dedicated to this area. Our study explores key hedonic motivations of virtual content shopping and how hedonic shopping value builds trust (trust in virtual content and trust in virtual retailers) that enhances the intention to pay for premium.

This research adopts a mixed-methods approach. Study 1 is qualitative; 19 semi-structured interviews were conducted with virtual game retail platform users. Study 2, based on the literature review and qualitative inquiry findings (obtained from Study 1), proposes a research model empirically validated by analyzing survey data administered to 437 online gamers from gaming zones, cybercafés and e-sports centers.

The results show that in-game shopping-related adventure-, gratification-, role- and idea-seeking motivations significantly influence gamers' perceived hedonic shopping value. In turn, perceived shopping value has a significant indirect effect through trust on gamers’ intention to pay for premium.

This research contributes to gaming literature by offering a comprehensive model that elucidates the role of hedonic shopping in increasing gamers’ trust, which explains purchase behavior in the virtual game retail context. The findings deepen the understanding of the game retailing landscape and offer strategies to build gamers’ trust, increase premium usage and retain existing spenders.

Product-as-a-Service (PaaS) has the potential to enable closed-loop supply chains (CLSC) and decrease environmental impact, but it is only applied on a small scale. The purpose of this paper is to explore and develop a framework of challenges and corresponding mitigations encountered by Business-to-Consumer (B2C) retailers when transitioning to PaaS.

Data collection drew on a qualitative interview study with two industry experts and four PaaS B2C retailers from different Dutch industries.

A framework was developed linking 26 challenges in eight clusters—financial, product-related, supply chain-related, consumer-related, human resources, research and development/technology, regulatory and industry-related—to 24 mitigations. The mitigations were elaborated, and theoretical insights for matching challenges with mitigations were provided.

This study expands PaaS literature to the generally under-researched retail context. It contributes to CLSC literature by applying it to a less-studied context, thereby revealing many supply chain-related challenges and mitigations encountered by B2C retailers.

The framework offers practical guidance to retail managers for overcoming or preventing challenges in PaaS, in their endeavours toward adopting environmentally sustainable practices.

The study creates awareness about environmental sustainability and the potential to reduce societal impact, in which a PaaS-enabled CLSC is one step.

Studying PaaS and CLSC in a retail context is timely and novel.

This study aims to identify the librarians’ readiness to leverage artificial intelligence for sustainable competence development and smart library services.

This study used a quantitative research design for addressing the objectives. The population consisted of librarians from the public and private sector universities of Pakistan. The data were analyzed by using Smart PLS software.

The analysis consisted of two major parts: first the assessment of measurement model and second the structural equation modeling analysis. A significant positive impact of AI adoption was found on the implementation smart library services. Findings revealed that behavioral intention motivated librarians to adopt AI tools in university libraries for the delivery of smart library services.

We applied quantitative method to carry out the study while future authors may conduct a systematic literature review on the same topic for offering a broader outlook.

It has provided practical contributions by providing a baseline for management bodies to construct policies for the successful adoption of AI in libraries for sustainable competence development of practicing librarians and implementation of smart library services.

The study has social implications too as AI integrated library services prove fruitful for society and digitally skilled librarians play a vital role for the promotion of reading and research culture in society.

To the best of the authors’ knowledge, this is the first study on librarians’ readiness to leverage artificial intelligence for the enhancement of digital literacy skills, sustainable competence development and smart library services in the context of Pakistan.

This study aims to identify the effects of artificial intelligence (AI) on university libraries and to reveal challenges associated with the adoption of AI-powered applications in libraries.

A systematic literature review (SLR) was applied to address the study’s objectives. The 25 most relevant seminal studies published in Scopus- and Web of Science-indexed journals were selected to conduct the study.

Findings revealed that AI has strong positive effects on university libraries. These effects included efficiency and promotion of library products, innovative library services, alignment of library services with the fourth industrial revolution (4IR), collection management and user services and transformation of library systems. Results also manifested that skills and knowledge barriers, financial and resource constraints and resistance to change created challenges to adopt AI-based services in university libraries.

This study has added valuable literature to the existing body of knowledge by conducting SLR on the basis of 25 most relevant research articles published in cite score and impact factor journals. It has provided practical implications by offering recommendations to adopt AI in university libraries. The study is a benchmark for policymakers, AI applications developers, higher education bodies, government representatives, university administration and library leadership to devise effective strategies and methods for the efficient adoption of AI in libraries. The study has also provided a framework to adopt AI applications in library settings.

Blockchain, a groundbreaking technology that recently surfaced, is under thorough scrutiny due to its prospective utility across different sectors. This research aims to delve into and assess the cognitive elements that impact the integration of blockchain technology (BT) within library environments.

Utilizing the Stimulus–Organism–Response (SOR) theory, this research aims to facilitate the implementation of BT within academic institution libraries and provide valuable insights for managerial decision-making. A two-staged deep learning structural equation modelling artificial neural network (ANN) analysis was conducted on 583 computer experts affiliated with academic institutions across various countries to gather relevant information.

The research model can correspondingly expound 71% and 60% of the variance in trust and adoption intention of BT in libraries, where ANN results indicate that perceived possession is the primary predictor, with a technical capability factor that has a normalized significance of 84%. The study successfully identified the relationship of each variable of our conceptual model.

Unlike the SOR theory framework that uses a linear model and theoretically assumes that all relationships are significant, to the best of the authors’ knowledge, it is the first study to validate ANN and SEM in a library context successfully. The results of the two-step PLS–SEM and ANN technique demonstrate that the usage of ANN validates the PLS–SEM analysis. ANN can represent complicated linear and nonlinear connections with higher prediction accuracy than SEM approaches. Also, an importance-performance Map analysis of the PLS–SEM data offers a more detailed insight into each factor's significance and performance.

The board structure (BS) is pivotal in modern corporate governance (CG). This study aims to investigate BS variables (BSIZE, BIND and chief executive officer [CEO] duality) and their correlation with risk-taking behavior indicators, enriching the understanding of how CG shapes financial institutions’ (FIs) decision-making in Pakistan.

By scrutinizing data from 67 financial entities listed on the Stock Exchange of Pakistan spanning from 2011 to 2022 through panel data regression techniques, the research emphasizes that BS holds a substantial influence over the risk tendencies exhibited by these firms.

Key findings suggest that board size has a positive influence, aligned with previous CG research. Smaller boards perform better and avoid excessive risk-taking, contrasting some negative relationship claims. More independent directors are recommended to curtail risk and financial disruption. Holding both CEO and chair roles reduces risk exposure, resonating with reputational and employment risk theory. It is essential to recognize that BS’s impact on risk-taking is nuanced and context-dependent.

Policymakers, scholars, practitioners and investors working in the market for financial companies might greatly benefit from the empirical findings of this study. Imposing mandates on FIs to uphold adequate capital reserves functions as a safeguard against unforeseen losses, thereby diminishing the probability of unwarranted risk-taking.

Prior studies in this domain predominantly focus on nonfinancial sectors. In addition, existing research often explores the relationship between BS and firm risk-taking solely within the banking sector, overlooking other FIs. This study contributes by using a comprehensive data set encompassing all types of FIs, thus extending the existing literature.

The purpose of this study is to examine the specific social media behaviours (SMB) that lead to major depressive disorder (MDD). The study also looks at the moderation effect of pandemic on social media usage among users.

Using a descriptive approach, the required data was collected from a sample of 629 social media users chosen through random sampling technique. An adopted structured online questionnaire was used to collect the data. The data collected was analysed by using univariate and multinomial regression techniques.

The findings of the study revealed that social media intensity, social media addiction (SMA), social media participation, social interaction and SMB had a positive impact on MDD, whereas social comparison had a negative impact. The pandemic situation has also been found to moderate the effect of social media usage on MDD.

This study will be supportive in disclosing behaviours and activities of students that impact their mental health adversely. This will also be helpful in dealing with specific stressors in the programs designed to cope with the depression. By adopting effective strategies to manage social media usage, the study would help to reduce the level of depressive symptoms among college students, significantly promoting healthy environments for students and, thus, contribute to social change.

Since the social media has both favourable and detrimental effects, the key for the users is to develop an awareness about the wise usage and to determine the alterations in the usage patterns that can help to reduce the behaviours associated with negative emotions and psychological distress.

The study aims to explore the moderation effect of renewable energy consumption (REC) on the relationship between foreign direct investment (FDI) inflows and carbon emission (CO₂). Furthermore, the study investigates the prevalence of rebound effect in energy efficiency for the top five FDI inbound destinations in the Asia-Pacific region.

The study uses a balanced panel data set spanning from 1995 to 2020 obtained from the World Bank Database. This paper used feasible generalized least squares (FGLS) as the primary method, and to ensure the robustness of the findings, this paper used the panels corrected standard errors (PCSE) model.

The findings reveal a negative relationship between FDI and CO₂ emissions and REC and CO₂ emissions. However, the moderation effect of REC on the relationship between FDI inflows and CO₂ emissions is positive, suggesting that when both FDI and REC increase simultaneously, carbon emissions also increase. This study attributes the observed positive moderation effect to the phenomenon known as the rebound effect.

FDI fosters environmental sustainability. Regions’ FDI policies can be guidelines for other nations aiming for similar outcomes. REC reduces CO₂ emissions, underlining renewable energy’s efficacy. However, positive moderation effect of REC on the relationship between FDI and CO₂ emissions highlights the necessity for balanced policies to prevent unintended consequences like the rebound effect.

The originality of this study lies in examining the prevalence of rebound effect in energy efficiency. Prior empirical studies have explored the relationship between REC and carbon emission and established that increased efficiency in renewable energy creates positive environmental and climate externalities. However, it is constrained by rebound effects and this has been ignored by previous studies.

Malaysian small and medium-sized enterprises (SMEs) are critical for economic development and meeting the sustainable development goals (SDGs); however, many struggle to survive in the long term. So, this study aims to present a model for sustainable growth that bridges the gap between desired growth and managerial competencies. By configuring university helix-induced crowdfunding and opportunity recognition competencies with industry helix-driven innovation, the study encourages a quadruple bottom line (QBL) strategy, helping SMEs attain competitiveness for sustainable growth.

This pilot study used a sequential mixed methods design and adhered to the pragmatic research paradigm. A survey of 52 SCORE-listed manufacturers yielded quantitative data, complemented by qualitative interviews with 7 SME decision makers. This study used NVivo 10 and SmartPLS 4.0 for the necessary analysis. In addition, an effective triangulation strategy has been implemented to explain causation among selected variables.

The findings show that opportunity recognition and crowdfunding are positively associated with SMEs’ ability to grow in a sustainable manner and that exploitative and explorative innovation also mediate those relationships. The qualitative part highlighted key insights for successfully applying this model in Malaysian SMEs. The interview results also suggest that corporate spirituality might help SMEs adopt sustainability-focused practices.

More research is required regarding both the methods and results of this pilot study. Although conducting a pilot study increases the likelihood of success in the main study, it does not ensure it.

This study equips Malaysian SMEs with a roadmap for achieving sustainable growth. The obtained findings indicate that Malaysian SMEs that develop strong crowdfunding and opportunity recognition competencies are more likely to achieve innovation-focused long-term survival. In addition, incorporating corporate spirituality can enhance their economic, social and environmental performance.

By supporting more innovation in SMEs, which can improve sustainability-oriented successes and support a healthy economic system, these findings may have a beneficial social change impact. The concept may also act as the foundation for SMEs’ promotion of the SDGs.

The study uniquely offers a holistic growth model for Malaysian SMEs founded on the helix-QBL understanding that explains a firm’s sustainability-focused competitive advantage.

The purpose of this paper is to determine the effect of the industrial sector, renewable energy consumption and nonrenewable energy consumption in Indonesia on the ecological footprint from 1990 to 2020 in the short and long term.

This paper uses vector error correction model (VECM) analysis to examine the relationship in the short and long term. In addition, the impulse response function is used to enable future forecasts up to 2060 of the ecological footprint as a measure of environmental degradation caused by changes or shocks in industrial value-added, renewable energy consumption and nonrenewable energy consumption. Furthermore, forecast error decomposition of variance (FEVD) analysis is carried out to predict the percentage contribution of each variable’s variance to changes in a specific variable. Granger causality testing is used to enhance the analysis outcomes within the framework of VECM.

Using VECM analysis, the speed of adjustment for environmental damage is quite high in the short term, at 246%. This finding suggests that when there is a short-term imbalance in industrial value-added, renewable energy consumption and nonrenewable energy consumption, the ecological footprint experiences a very rapid adjustment, at 246%, to move towards long-term balance. Then, in the long term, the ecological footprint in Indonesia is most influenced by nonrenewable energy consumption. This is also confirmed by the Granger causality test and the results of FEVD, which show that the contribution of nonrenewable energy consumption will be 10.207% in 2060 and will be the main contributor to the ecological footprint in the coming years to achieve net-zero emissions in 2060. In the long run, renewable energy consumption has a negative effect on the ecological footprint, whereas industrial value-added and nonrenewable energy consumption have a positive effect.

For the first time, value added from the industrial sector is being used alongside renewable and nonrenewable energy consumption to measure Indonesia’s ecological footprint. The primary cause of Indonesia’s alarming environmental degradation is the industrial sector, which acts as the driving force behind this issue. Consequently, this contribution is expected to inform the policy implications required to achieve zero carbon emissions by 2060, aligned with the G20 countries’ Bali agreement of 2022.