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This study aims to examine the mediating role of product judgement in the relationship between electronic word-of-mouth (eWOM) and purchase intention. Additionally, it explores the moderating effects of source credibility and consumer ethnocentrism on the relationship between eWOM and product judgement, with a specific focus on Halal products. We utilise the Elaboration Likelihood Model (ELM) to investigate how individuals navigate the processing of information, distinguishing between central and peripheral routes. This exploration aims to enhance our understanding of how the ELM framework influences product judgement and purchase intention in the context of eWOM, with a focus on Halal products.

To achieve these objectives, an online survey was conducted in the United Kingdom. The study employed a moderated-mediation model, analysed using PLS-SEM.

The findings highlight the significant role of source credibility in the central route of information processing and purchase judgements. This study confirms that Halal product judgement fully mediates the relationship between eWOM and purchase intention. Additionally, it reveals that higher source credibility amplifies the impact of eWOM on consumer judgement. However, no significant moderating effect of consumer ethnocentrism on the relationship between eWOM and product judgement was observed in this context.

This study enhances our understanding of how Halal products are adopted in non-Muslim societies, shedding light on persuasive processes. Additionally, it refines the ELM in the context of cross-cultural consumer behaviour. The findings underscore the importance of prioritising source credibility in communication to shape information evaluation and persuasion.

This paper aims to explore the development of investment decision tools by understanding the rationality behind the disposition effect. We suspect that not all disposition decisions are irrational. The decisions should be evaluated based on the bounded rationality of the individuals’ target and tolerance level, which is not covered in previous literature. Adding the context of individual preference (target and tolerance) in their decision could improve the classic measurement of disposition effect.

The laboratory web experiment is prepared to collect the responses in holding and selling the stocks within 14 days. Two groups of Gen Z investors are observed. The control group makes a decision based on their judgment without any system recommendation. In contrast, the second group gets help inputting their target and tolerance. Furthermore, the framing effect is also applied as a reminder of their target and tolerance to induce more holding decisions on gain but selling on loss.

The framing effect is adequate to mitigate the disposition effect but only at the early day of observation. Bounded rationality explains the rationality of liquidating the gain because the participants have reached their goal. The framing effect is not moderated by days to affect the disposition effect; over time, the disposition effect tends to be higher. A new measurement of the disposition effect in the context of bounded rationality is better than the original disposition effect coefficient.

Gen Z investors need a system aid to help their investment decisions set their target and tolerance to mitigate the disposition effect. Investment firms can make a premium feature based on real-time market data for investors to manage their assets rationally in the long run. Bounded rationality theory offers more flexibility in understanding the gap between profit maximization and irrational decisions in behavioral finance. The government can use this finding to develop a suitable policy and ecosystem to help beginner investors understand investment risk and manage their assets based on subjective risk tolerance.

The classic Proportion Gain Realized (PGR) and Proportion Loss Realized (PLR) measurements cannot accommodate several contexts of users’ targets and tolerance in their choices, which we argue need to be re-evaluated with bounded rationality. Therefore, this article proposed new measurements that account for the users’ target and tolerance level to evaluate the rationality of their decision.

Autonomous vehicles (AVs) have the potential to transform the infrastructure, mobility and social well-being paradigms in New Zealand (NZ) amid its unprecedented population and road safety challenges. But, public acceptance, co-evolution of regulations and AV technology based on interpersonal and institutional trust perspectives pose significant challenges. Previous theories and models need to be more comprehensive to address trust influencing autonomous driving (AD) factors in natural settings. Therefore, this study aims to find key AD factors corresponding to the chain of human-machine interaction (HMI) events happening in real time and formulate a guiding framework for the successful deployment of AVs in NZ.

This study utilized a comprehensive literature review complemented by an AV users’ study with 15 participants. AV driving sprints were conducted on low, medium and high-density roads in Auckland, followed by 15 ideation workshops to gather data about the users’ observations, feelings and attitudes towards the AVs during HMI.

This research study determined nine essential trust-influencing AD determinants in HMI and legal readiness domains. These AD determinants were analyzed, corresponding to eight AV events in three phases. Subsequently, a guiding framework was developed based on these factors, i.e. human-machine interaction autonomous driving events relationship identification framework (HMI-ADERIF) for the deployment of AVs in New Zealand.

This study was conducted only in specific Auckland areas.

This study is significant for advanced design research and provides valuable insights, guidelines and deployment pathways for designers, practitioners and regulators when developing HMI Systems for AD vehicles.

This study is the first-ever AV user study in New Zealand in live traffic conditions. This user study also claimed its novelty due to AV trials in congested and fast-moving traffic on the four-lane motorway in New Zealand. Previously, none of the studies conducted AV user study on SUV BMW vehicle and motorway in real-time traffic conditions; all operations were completely autonomous without any input from the driver. Thus, it explored the essential autonomous driving (AD) trust influencing variables in human factors and legal readiness domains. This research is also unique in identifying critical AD determinants that affect the user trust, acceptance and adoption of AVs in New Zealand by bridging the socio-technical gap with futuristic research insights.

The purpose of this study is to propose a financial distress prediction (FDP) model and method suitable for listed Indian small and medium enterprises (SMEs).

A three-part screening criteria similar to Platt and Platt (2006) was tested independently and jointly on Indian SMEs using statistically significant financial variables. Five stepwise multiple discriminant analysis (MDA) models were developed and the best-performing model was further compared against seminal models to check for robustness.

Model C2 developed under Criterion C which stated “if net income before special items is negative in any given year the firm is considered as ‘unwell’” proved robust and effective.

The proposed model identified the importance of profitability and efficiency ratios over leverage ratios in determining financial distress and therefore, have implications for SME owners/managers and shareholders.

To augment sales revenue, B2B digital start-ups aim to create and sustain commercial relationships with industry incumbents. However, since these incumbents have traditionally struggled with implementing disruptive digital artifacts, most studies have almost exclusively concentrated on their challenges, leaving the digital start-ups' side underexplored. Therefore, this study seeks to understand how digital start-ups navigate digital implementation (DI) hardships to ultimately achieve digital entrepreneurship success.

An abductive explanatory multi-case study of four industries that pose a variety of implementation challenges for B2B digital start-ups (agriculture, insurance, real estate and construction, and healthcare) was conducted using data collected from 40 interviews with Israeli experts and relevant digital data observations.

This study articulates two main observations. (1) Throughout their journeys, digital start-ups have utilized newly created and/or refined dynamic capabilities (DC) to successfully implement their digital artifacts. Simultaneously, successful DI has enabled digital start-ups to create new DC or sustain and evolve current DC. (2) We provide empirical evidence outlining how digital start-ups using continuous learning have combined causation and effectuation logic throughout their DI journeys.

This study answers a call to explore more explicit digital-related drivers (i.e. DI) for digital entrepreneurship success by studying a highly-ranked country on the Global Entrepreneurship Index (GEI) to achieve this. Moreover, it illustrates how digital start-ups evolve throughout their commercial relationships with industry incumbents, thereby enabling an effective approach for successful DI. Such an approach can be considered very valuable for both practitioners and policymakers. Consequently, it advances digital entrepreneurship as an independent research topic.

The purpose of this study is to identify and analyze the barriers associated with the adoption of Industry 4.0 technologies in agricultural supply chains.

The study initially identified thirteen barriers by conducting a literature review and semi-structured interviews with key stakeholders. Subsequently, these barriers were validated and modeled using an integrated Fuzzy Delphi-ISM approach. Finally, MICMAC analysis was employed to categorize the barriers into distinct clusters.

The results provide considerable insights into the hierarchical structure and complex interrelationships between the barriers as well the driving and dependence power of barriers. Lack of information about technologies and lack of compatibility with traditional methods emerged as the two main barriers which directly and indirectly influence the other ones.

The robust hybrid Fuzzy Delphi and ISM techniques used in this study can serve as a useful model and benchmark for similar studies probing the barriers to Industry 4.0 adoption. From a theoretical standpoint, this study expands the scope of institutional theory in explaining Industry 4.0 adoption barriers.

The study is timely for the post-COVID-19 recovery and growth of the agricultural sector. The findings are helpful for policymakers and agriculture supply chain stakeholders in devising new strategies and policy interventions to prioritize and address Industry 4.0 adoption barriers.

It is the first comprehensive, multi-country and multi-method empirical study to comprehensively identify and model barriers to Industry 4.0 adoption in agricultural supply chains in emerging economies.

The purpose of this paper is to investigate risk propagation and resilience in the agribusiness supply chain (ASC).

The paper undertakes a systematic literature review (SLR). Overall, 94 articles from six databases published between 2000 and 2022 underwent descriptive and thematic analysis.

There is a lack of research on risk propagation and resilience in the ASC for more than two decades. Accordingly, this research fills the gap in the extant literature by advancing the construct of risk propagation and resilience in the ASC and developing a framework proposing directions in risk propagation and resilience in ASC research.

Firstly, only the Web of Science and Scopus databases were mostly used as primary sources while other databases were used as secondary sources to validate search results. Secondly, SLR is based on the peer-reviewed articles, books and conference papers; other non-academic sources relevant to the topic were not included in this paper.

The paper offers a set of constructs for understanding risk propagation and resilience in the ASC, develops a framework proposing directions in risk propagation and resilience in the ASC research and recommends three key themes for future research directions, namely, keep updated with recent constructs of risk propagation and resilience in the ASC, conduct case studies based on empirical studies to determine the current risk dependency and propagation in the ASC and conduct case studies based on empirical studies to determine resilience and sustainability in the ASC.

Expressing views on organizational information security (IS) by employees is vital for improving security processes, policies and trainings, while non-communication may conceal the true state of the human factor of IS and lead to security breaches. The purpose of this paper is to introduce the concept of opinion expressing about organizational IS, provide an explanatory model based on the theory of spiral of silence and offer its empirical validation.

Data from a web-based survey among the employees of one the universities in the European Union (n = 504) was analyzed with regression analysis to investigate the proposed hypotheses.

The study reveals that employees with positive opinions about IS will be more willing to share their opinions with coworkers and management. However, when employees perceive that their pro-IS opinions are not shared by other coworkers, they will remain silent, which increases the risk of problematic opinions spreading throughout the organization.

The study highlights the need to focus on the communication perspectives of organizational information security, an area often overlooked in the human factor of information security research.

The results highlight the need to examine the gap between the dominant climate of opinion about IS in the organization and the display of compliant IS behaviors in order to strengthen IS endeavors. Organizations are encouraged to facilitate open dialogue about IS processes, policies and training and implement mechanisms for considering employees’ feedback in order to improve the organization’s IS.

The study contributes to a growing body of research that moves beyond viewing employees merely as subjects of compliance, recognizing instead their agency in IS issues that can enhance organizational resilience. To the best of the authors’ knowledge, this is the first study to apply the spiral of silence theory in the IS field, thereby helping to overcome the lack of communication science perspectives in organizational IS research.

Growing research attention has been given to both the circular economy and digitalisation in accounting research in recent years, but there are few studies exploring how digital tools are used to develop, analyse and respond to information for circular decision-making in industrial organisations. Therefore, this paper addresses how the data from digital technologies are leveraged in the aftermarket of an industrial firm for circular control.

The paper develops an analytical framework that is then used to frame the findings through a single case study of an international heavy equipment manufacturer for circular control.

The case provides examples of how digital technologies are used for circular control, framed within the analytical model as the key contribution. The study illustrates the different ways through which the accounting information from such technologies supports the service marketing function through circular control and the types of controls needed for this.

Managers in large industrial organisations should ensure customer-facing staff have adequate digital competences and knowledge of circular products and services for marketing, product design improvements and material recovery that can help decrease costs and improve customer satisfaction. The digital systems need to be integrated with upstream and downstream partners.

Understanding the transition towards increasingly circular product-service systems in industrial firms is important for current and future generations.

The originality lies in providing an empirical example of how digital technologies can be used to facilitate circular control and support the service marketing function in the aftermarket of an industrial firm.

From a firm-centric perspective, this study aims to elaborate on the types of servitisation strategies that can support a firm’s circular ambitions by asking: What is the role of servitisation in narrowing, slowing and/or closing resource loops? And, how are resources and capabilities arranged to provide such strategic circular service offerings?

Drawing on the experiences of an international manufacturing company from a dynamic capabilities perspective, the study offers an analytical framework that goes inside the firm’s operationalisation of its service offerings to support circularity in terms of the strategic decisions made. This framework is later used to frame the findings.

The study highlights the case-specific feedback loops and capabilities needed to support circular transitions. Various resource and innovation strategies for circularity are combined along customer interfaces and in partnership with upstream actors. Yet, open innovation strategies are conditioned by physical distance to provide circular services in remote areas.

The main contributions are empirical, analytical, conceptual and practical. The servitisation framework for circularity connects prior servitisation-circularity research and provides an analytical tool for framing future studies. The study also expands the definition of open innovation in that closed innovations for circularity can be achieved through “open” information exchange in knowledge networks, as well as provides advice for similar large manufacturing companies.

This study focuses on the strategic choices made by industrial firms for circular service provision and emphasises the environmental benefits from such choices, in addition to the economic and customer benefits covered in extant servitisation research.