Search results

This paper aims to identify and classify the parameters that construct the input, processes, output, productivity and outcome variables that affect performance. These parameters are used in the evaluation model to measure research performance in universities so that they can be used as the basis for making leadership policies both at the national and institutional levels.

The design of this research is a quantitative research method using a survey questionnaire that was sent to the heads of research institutions at universities in Indonesia. To obtain these parameters, a test for determining the value of the loading factor was used.

The authors found that input variable parameters consisted of 10 parameters; process variable consisted of 22 parameters; output variable parameters consisted of 8 parameters; productivity variable consisted of 4 parameters; and outcome variable parameters consisted of 10 parameters.

One approach to obtain parameters is through systems theory, where every element that makes up the organization contributes to the achievement of goals. This study attempted to develop parameters in the performance appraisal model of systems theory-based research institutions that are adapted to trends in the direction of research in universities. These parameters are based on aspects of input, process, output, productivity and outcome.

Although virtual anchors have emerged as potent marketing tools, their acceptance by consumers is controversial. Specifically, the relative efficacy of selecting an all-human-like or animal-human-like virtual anchor is not well-defined. However, anthropomorphic visual cues are vital in enhancing live streaming. This study aims to analyze the disparate effects of an animal-human-like or all-human-like virtual anchor on purchase intention as well as evaluate the possible underlying influential mechanisms and boundary conditions.

In this research, three different studies were carried out to elucidate the impact of virtual anchors on purchase intention. Study 1 evaluated the core impact of an animal-human-like and all-human-like virtual anchor on purchase intention, as well as the mediating role of perceived warmth and competence. Studies 2 and 3 were then performed to investigate the moderating impacts of product type and certainty of consumer needs, respectively. Furthermore, research data for these studies was collected using the Credamo tool and analyzed via SPSS, using PROCESS for moderation and mediation analyses.

The research findings indicate that virtual anchors can trigger purchase intention, with perceived warmth and competence acting as mediating factors. Based on the utilitarian products and high certainty of consumer needs, the influence of perceived competence on purchase intention is augmented. Therefore, an all-human-like virtual anchor increases purchase intention. In contrast, the impact of perceived warmth on purchase intention is supplemented for hedonic products and low certainty of consumer needs. Thus, an animal-human-like virtual anchor increases purchase intention.

This research study evaluated consumer reactions to all-human-like and animal-human-like virtual anchors for different product types and the certainty of consumer needs to optimize the comprehension of a virtual anchor. Furthermore, the assessment of the mediating roles of perceived warmth and competence provided valuable insights into the influential mechanisms by which virtual anchors affect purchase intention. Moreover, this study provided managerial implications to guide retailers and brands on the strategic adoption of virtual anchors to enhance purchase intention based on the product type and the certainty of consumer needs.

Conceptual and empirical research over the past 20 years has moved the social media (SM) literature beyond the embryotic stage to a well-developed academic discipline. As the lead article in the special issue in the Journal of Research in Interactive Marketing on Cutting-Edge Research in Social Media and Interactive Marketing, this review and agenda article has two key goals: (1) to review key SM and interactive marketing research over the past three years and (2) to identify the next wave of high priority challenges and research opportunities.

Given the “cutting-edge” research focus of the special issue, this review and research agenda paper focused on articles published in 25 key marketing journals between January 2021 and March 2024. Initially, the search request was for articles with “social media, social selling, social commerce” located in the article title, author-selected key words and journal-selected keywords. Later, we conducted searches based on terminology from articles presented in the final review. In total, over 1,000 articles were reviewed across the 25 journals, plus additional ones that were cited in those journals that were not on the initial list.

Our review uncovered eight key content areas: (1) data sources, methodology and scale development; (2) emergent SM technologies; (3) artificial intelligence; (4) virtual reality; (5) sales and sales management; (6) consumer welfare; (7) influencer marketing; and (8) social commerce. Table I provides a summer of key articles and research findings for each of the content areas.

As a literature review and research agenda article, this paper is one of the most extensive to date on SM marketing, and particularly with regard to emergent research over the past three years. Recommendations for future research are integrated through the paper and summarized in Figure 2.

Consumer welfare is one of the eight emergent content areas uncovered in the literature review. Specific focus is on SM privacy, misinformation, mental health and misbehavior.

Carbon reduction in the construction supply chain can critically affect the construction industry’s transition to an environmentally sustainable one. However, implementing carbon reduction in all parties is restricted because of the poor understanding of the drivers influencing the low-carbon construction supply chain (LCCSC). The purpose of this paper is to systematically identify the drivers of LCCSC, analyze their causality, and prioritize the importance of their management.

A decision-making analysis process was developed using an integrated decision-making trial and evaluation laboratory (DEMATEL)–analytical network process (ANP). First, the hierarchical drivers of the LCCSC were identified through a literature review. The DEMATEL method was subsequently applied to analyze the interactions between the drivers, including the direction and strength of impact. Finally, the ANP analysis was used to obtain the drivers’ weights; consequently, their priorities were established.

Various factors with complex interactions drive LCCSC. With respect to their influence relationships, incentive policy, regulatory policy, consumers’ low-carbon preference, market competition, supply chain performance, and managers’ low-carbon awareness have more significant center degrees and are cause drivers. Their strong correlations and influence on other drivers should be noticed. In terms of weights in the driver system, regulatory policy, consumers’ low-carbon preference, supply chain performance, and incentive policy are the key drivers of LCCSC and require primary attention. Other drivers, such as supply chain collaboration, employee motivation, and public participation, play a minor driving role with less management priority.

Despite some contributing studies with localized perspectives, the systematic analysis of LCCSC drivers is limited, especially considering their intricate interactions. This paper establishes the LCCSC driver system, explores the influence relationships among the drivers, and determines the key drivers. Hence, it contributes to the sustainable construction supply chain domain by enabling decision-makers and practitioners to systematically understand the drivers of LCCSC and gain management implications on priority issues with limited resources.

This study aims to investigate the drivers of bank automation system performance expectancy compared to that of bank employees. The purpose is to shed light on the role played by consumers' cognitive schema on automation that is the perfect automation schema (PAS).

A survey was administered to about 500 Italian subjects to measure their PAS; financial knowledge, anxiety, and security; and sociodemographic and socioeconomic variables. Ordered probit regressions and an instrumental variable two-stage least squares regression are run.

The analyses reveal that cognitive schemas play a crucial role in consumer expectations in banking. Individuals with stronger PAS tend to have more positive expectations about bank automation performance compared to employee performance. Financial anxiety and knowledge positively affect bank automation performance expectancy while women, older people, and financially insecure subjects have poor expectations of automated banking systems.

This study extends the understanding of key consumer characteristics that affect bank automation performance expectancy compared to that of bank employees in services delivery in the Italian context. Moreover, it provides useful results for researchers, practitioners, banking institutions, and regulators.

This paper aims to explain the factors shaping collective action within low-cost housing communities, focusing on parcel holders, through the utilisation of an expanded institutional analysis development (IAD) framework, which extends upon Ostrom’s foundational framework. Additionally, the paper explores four different property management approaches accessible to these communities.

The research employed a mixed-method approach comprising four sequential steps. Firstly, a quantitative inquiry entailed a questionnaire survey administered to 633 parcel holders across four low-cost housing schemes, aimed at discerning factors influencing collective action. Subsequently, a qualitative investigation involved face-to-face interviews with key stakeholders to elucidate the contributing factors of collective action, with a specific focus on Nursa Kurnia (a successful low-cost housing scheme comprising 200 units), accessible via Kuala Lumpur Middle Ring Road II. Thirdly, the study explored the social practice of “commoning the governance”. Lastly, the paper advocated for housing policy interventions, specifically proposing government subsidies for lower-income parcel holders.

Exemplified by the success of Nursa Kurnia, the research findings emphasised the importance of shifting local management’s mindset from a zero-sum approach to a win-win perspective. It highlighted the pivotal role of four factors (resource system, governance system, context and historical development) in shaping collective action and fostering improved property management practices. Moreover, the study highlighted the potential of “commoning the governance” as a new approach capable of addressing collective action challenges in low-cost housing management, presenting a promising avenue for future endeavours.

As more studies utilising the expanded IAD framework become available in the future, there is potential for further refinement and enhancement of the framework.

This study offers valuable insights for policymakers, property developers, local management and local communities, shedding light on challenges associated with the self-organisation of shared resources. Moreover, it highlights the potential of “commoning the governance” as a new property management approach to mitigate the impact of collective action problems.

The well-being of society’s most vulnerable segment is indicative of the overall societal health. This underscores the significance of addressing the interests and needs of these lower-income groups within the broader social context.

Exploring collective action within the context of self-organising low-cost housing, the study delves into an area marked by persistent challenges like free-riding tendencies and vandalism. Despite significant attention given to collective action issues in the past, the novel approach of “commoning the governance” remains unexamined in the realm of low-cost housing maintenance and management.

Blockchain for energy trading is a trending research area in the current context. However, a noticeable gap exists in the review articles focussing on solar energy trading with blockchain technology. Thus, this study aims to systematically examine and synthesise the existing research on implementing blockchain technology in sustainable solar energy trading.

The study pursued a systematic literature review to achieve its aim. The data extraction process focussed on the Scopus and Web of Science (WoS) databases, yielding an initial set of 129 articles. Subsequent screening and removal of duplicates led to 87 articles for bibliometric analysis, utilising VOSviewer software to discern evolutionary progress in the field. Following the establishment of inclusion and exclusion criteria, a manual content analysis was conducted on a subset of 19 articles.

The results indicated a rising interest in publications on solar energy trading with blockchain technology. Some studies are exploring the integration of new technologies like machine learning and artificial intelligence in this domain. However, challenges and limitations were identified, such as the absence of real-world solar energy trading projects.

This study offers a distinctive approach by integrating bibliometric and manual content analyses, a methodology seldom explored. It provides valuable recommendations for academia and industry, influencing future research and industry practices. Insights include integrating blockchain into solar energy trading and addressing knowledge gaps. These findings advance societal goals, such as transitioning to renewable energy sources (RES) and mitigating carbon emissions, fostering a sustainable future.

Supermarket promotions typically use a standard label, which displays the regular price, discounted price and discounted unit price. Visits to supermarkets across multiple countries found that none used a price label that also contains the regular (i.e. pre-discounted) unit price. This study aims to investigate the effectiveness of a dual unit-price label that includes the regular unit price as a reference price, and what underpins its efficacy in enhancing promotion attractiveness.

The authors executed four studies, supported by three supplemental studies. Study 1 established external validity through a natural instore experiment. Studies 2 and 3 tested the dual unit-price label with different pack sizes and assortment sizes, respectively. Finally, Study 4 tested the underpinning mechanism of the efficacy of the dual unit-price label.

In Study 1, daily sales records over four weeks showed that dual unit-price label promotions had larger sales volume than standard-label promotions. Study 2 showed a larger pack size, a heuristic cue for greater economy and increased preference for dual unit-price label promotions. Study 3 similarly found that the dual unit-price label was preferred more as cognitive load was increased by assortment size. Finally, Study 4 demonstrated the dual processing of the dual unit-price label, using a conscious preference measure (information provided) and an unconscious implicit attitude test.

Unit-price research has mainly considered a cognitive process. The authors demonstrated the importance of considering a heuristic process.

Supermarkets can use this simple and yet effective tool to improve promotion effectiveness.

This study demonstrates that the dual unit-price label is a new and easy tool to enhance sales promotions, which academic research and managerial practice had never considered previously.

The purpose of this paper is to investigate students' adoption intention (ADI) and actual usage (ATU) of artificial intelligence (AI)-based teacher bots (T-bots) for learning using technology adoption model (TAM) and context-specific variables.

A mixed-method design is used wherein the quantitative and qualitative approaches were used to explore the adoption of T-bots for learning. Overall, 45 principals/directors/deans/professors were interviewed and NVivo 8.0 was used for interview data analysis. Overall, 1,380 students of higher education institutes were surveyed, and the collected data was analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique.

The T-bot's ADI’s antecedents found were perceived ease of use, perceived usefulness, personalization, interactivity, perceived trust, anthropomorphism and perceived intelligence. The ADI influences the ATU of T-bots, and its relationship is negatively moderated by stickiness to learn from human teachers in the classroom. It comprehends the insights of senior authorities of the higher education institutions in India toward the adoption of T-bots.

The research provides distinctive insights for principals, directors and professors in higher education institutes to understand the factors affecting the students' behavioral intention and use of T-bots. The developers and designers of T-bots need to ensure that T-bots are more interactive, provide personalized information to students and ensure the anthropomorphic characteristics of T-bots. The education policymakers can also comprehend the factors of T-bot adoption for developing the policies related to T-bots and their implications in education.

T-bot is a new disruptive technology in the education sector, and this is the first step in exploring the adoption factors. The TAM model is extended with context-specific factors related to T-bot technology to offer a comprehensive explanatory power to the proposed model. The research outcome provides the unique antecedents of the adoption of T-bots.

This study aims to fabricate a multifunctional electromagnetic interference (EMI) shielding composite fabric with simultaneous high-efficiency photothermal conversion and Joule heating performances.

A multifunctional polypyrrole (PPy) hydrogel/multiwalled carbon nanotube (MWCNT)/cotton EMI shielding composite fabric (hereafter denoted as PHMC) was prepared by loading MWCNT onto tannin-treated cotton fabric, followed by in situ crosslinking-polymerization to synthesize three-dimensional (3D) conductive networked PPy hydrogel on the surface of MWCNT-coated cotton fabric.

Benefiting from the unique interconnected 3D networked conductive structure of PPy hydrogel, the obtained PHMC exhibited a high EMI-shielding effectiveness vale of 48 dB (the absorbing electromagnetic wave accounted for 84%) within a large frequency range (8.2–12.4 GHz). Moreover, the temperature of the laminated fabric reached 54°C within 900 s under 15 V, and it required more than 100 s to return to room temperature (28.7°C). When the light intensity was adjusted to 150 mW/cm², the PHMC temperature was about 38.2°C after lighting for 900 s, indicating high-efficiency electro-photothermal effect function.

This paper provides a novel strategy for designing a type of multifunctional EMI shielding composite fabric with great promise for wearable smart garments, EMI shielding and personal heating applications.