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Users' voluntary forwarding behavior opens a new avenue for companies to promote their brands and products on social networking sites (SNS). However, research on voluntary information disseminators is limited. This paper aims to bring an in-depth understanding of voluntary disseminators by answering the following questions: (1) What is the underlying mechanism by which some users are more enthusiastic to voluntarily forward content of interest? (2) How to identify them? We propose a theoretical model based on the Elaboration-Likelihood Model (ELM) and examine three types of factors that moderate the effect of preference matching on individual forwarding behavior, including personal characteristics, tweet characteristics and sender–receiver relationships.

Via Twitter API, we randomly crawled 1967 Twitter users' data to validate the conceptual framework. Each user’s original tweets and retweeted tweets, profile data such as the number of followers and followees and verification status were obtained. The final corpus contains 163,554 data points composed of 1,634 valid twitterers' retweeting behavior. Tweets produced by these core users' followees were also crawled. These data points constitute an unbalanced panel data and we employ different models — fixed-effects, random-effects and pooled logit models — to test the moderation effects. The robustness test shows consistency among these different models.

Preference matching significantly affects users' forwarding behavior, implying that SNS users are more likely to share contents that align with their preferences. In addition, we find that popular users with lots of followers, heavy SNS users who author tweets or forward other-sourced tweets more frequently and users who tend to produce longer original contents are more enthusiastic to disseminate contents of interest. Furthermore, interaction strength has a positive moderating effect on the relationship between preference matching and individuals' forwarding decisions, suggesting that users are more likely to disseminate content of interest when it comes from strong ties. However, the moderating effect of perceived affinity is significantly negative, indicating that an online community of individuals with many common friends is not an ideal place to engage individuals in sharing information.

This work brings about a deep understanding of users' voluntary forwarding behavior of content of interest. To the best of our knowledge, the current study is the first to examine (1) the underlying mechanism by which some users are more likely to voluntarily forward content of interest; and (2) how to identify these potential voluntary disseminators. By extending the ELM, we examine the moderating effect of tweet characteristics, sender–receiver relationships as well as personal characteristics. Our research findings provide practical guidelines for enterprises and government institutions to choose voluntary endorsers when trying to engage individuals in information dissemination on SNS.

The aim of this study is to present an overview of sustainable practices in the development of waterproof breathable fabrics for garments. It aims to provide insights into the current state of academic research in this domain and identify and analyze major sustainable trends in the field.

This study conducts a thorough examination of research publications sourced from the Scopus database spanning the years 2013–2023 by employing a systematic approach. The research utilizes both descriptive analysis and content analysis to identify trends, notable journals and leading countries in sustainable waterproof breathable fabric development.

The study reveals a notable increase in studies focusing on sustainable approaches in the development of waterproof breathable fabrics for garments. Descriptive analysis highlights the most prominent journal and leading country in terms of research volume. Content analysis identifies four key trends: minimizing chemical usage, developing easily degradable materials, creating fabrics promoting health and well-being and initiatives to reduce energy consumption.

The main limitation of this research lies in its exclusive reliance on the Scopus database.

The insights derived from this study offer practical guidance for prospective researchers interested in investigating sustainable approaches to developing waterproof breathable fabric for garments. The identified trends provide a foundation for aligning research endeavors with contemporary global perspectives, facilitating the integration of sustainable methodologies into the garment industry.

This systematic literature review contributes original insights by synthesizing current research trends and outlining evolving sustainable practices in the development of waterproof breathable fabrics. The identification of key focus areas adds a novel perspective to existing knowledge.

This study aims to examine the blockchain landscape in supply chain management by drawing insights from academic and industry literature. It identifies the key drivers, categorizes the products involved and highlights the business values achieved by early adopters of blockchain technology within the supply chain domain. Additionally, it explores fingerprinting techniques to establish a robust connection between physical products and the blockchain ledger.

The authors combined the interpretive sensemaking systematic literature review to offer insights into how organizations interpreted their business challenges and adopted blockchain technology in their specific supply chain context; content analysis (using Leximancer automated text mining software) for concept mapping visualization, facilitating the identification of key themes, trends and relationships, and qualitative thematic analysis (NVivo) for data organization, coding and enhancing the depth and efficiency of analysis.

The findings highlight the transformative potential of blockchain technology and offer valuable insights into its implementation in optimizing supply chain operations. Furthermore, it emphasizes the importance of product provenance information to consumers, with blockchain technology offering certainty and increasing customer loyalty toward brands that prioritize transparency.

This research has several limitations that should be acknowledged. First, there is a possibility that some relevant investigations may have been missed or omitted, which could impact the findings. In addition, the limited availability of literature on blockchain adoption in supply chains may restrict the scope of the conclusions. The evolving nature of blockchain adoption in supply chains also poses a limitation. As the technology is in its infancy, the authors expect that a rapidly emerging body of literature will provide more extensive evidence-based general conclusions in the future. Another limitation is the lack of information contrasting academic and industry research, which could have provided more balanced insights into the technology’s advancement. The authors attributed this limitation to the narrow collaborations between academia and industry in the field of blockchain for supply chain management.

Practitioners recognize the potential of blockchain in addressing industry-specific challenges, such as ensuring transparency and data provenance. Understanding the benefits achieved by early adopters can serve as a starting point for companies considering blockchain adoption. Blockchain technology can verify product origin, enable truthful certifications and comply with established standards, reinforcing trust among stakeholders and customers. Thus, implementing blockchain solutions can enhance brand reputation and consumer confidence by ensuring product authenticity and quality. Based on the results, companies can align their strategies and initiatives with their needs and expectations.

In essence, the integration of blockchain technology within supply chain provenance initiatives not only influences economic aspects but also brings substantial social impacts by reinforcing consumer trust, encouraging sustainable and ethical practices, combating product counterfeiting, empowering stakeholders and contributing to a more responsible, transparent and progressive socioeconomic environment.

This study consolidates current knowledge on blockchain’s capacity and identifies the specific drivers and business values associated with early blockchain adoption in supply chain provenance. Furthermore, it underscores the critical role of product fingerprinting techniques in supporting blockchain for supply chain provenance, facilitating more robust and efficient supply chain operations.

This study aims to investigate the manufacturing reshoring decision-making content from an Eclectic Paradigm perspective.

Data were collected through a six-step systematic literature review on factors influencing manufacturing reshoring decision-making. The review is based on 100 peer-reviewed journal papers discussing reshoring decision-making contents published from 2009 to 2022.

In total, 80 decision factors were extracted and then categorized into resource-seeking (8%), market-seeking (11%), efficiency-seeking (41%) and strategic asset-seeking (16%) advantages. Additionally, 24% of these were identified as hybrid, which means that they were classified into multiple categories. Some decision factors were further identified as reshoring influencing factors (i.e. drivers, enablers and barriers).

Scholars need to consider what other theories can be used or developed to identify and evaluate the decision factors (determinants) of manufacturing reshoring as well as how currently adopted theory can be further advanced to create clearer and comprehensive theoretical frameworks.

This research underscores the importance of developing clearer and more comprehensive theoretical frameworks. For practitioners, understanding the multifaceted nature of decision factors could enhance strategic decision-making regarding reshoring initiatives.

To the best of the authors’ knowledge, this is the first study to investigate the value and practicality of the Eclectic Paradigm in categorizing factors in manufacturing reshoring decision-making content and presents in-depth theoretical classifications. In addition, it bridges the gap between decision factors and influencing factors in the decision-making content research realm.

This study aims to explore how firms can enhance their innovation processes by effectively utilizing external knowledge and employing digital technologies. Specifically, it emphasizes the role of absorptive capacity (ACAP) in external knowledge acquisition and assimilation (potential ACAP), as well as transformation and exploitation (realized ACAP), highlighting the necessity of equipping firms with digital technologies to support ACAP activities.

To achieve the research purpose, we conducted a structured literature review of academic papers sourced from Scopus-Elsevier.

The key findings encompass the identification of common digital technologies supporting ACAP and explore how these technologies contribute to knowledge acquisition, assimilation, transformation and exploitation. The main results show that social media and online communities are the most studied technologies in relation to ACAP activities. Research predominantly centres on potential ACAP – with acquisition activity more studied than assimilation – rather than realized ACAP – with only social media and online communities demonstrating full support for transformation and exploitation activities.

This research represents a pioneering joint study of ACAP and digital technologies, advancing understanding beyond organizational perspectives and expanding open innovation literature by integrating ACAP role in technology collaborations. A call for qualitative investigations into the relationship between digital technologies and ACAP emerged.

The findings offer valuable guidance to innovation managers, aiding them in selecting appropriate digital technologies to strengthen ACAP activities.

This work’s uniqueness lies in bridging the gaps between open innovation, ACAP and digital technologies, which are often studied in isolation.

In today’s complex and globalised business setting, Australian clothing retailers are ever more vulnerable to supply chain disruptions. Supply chain resilience reduces the effect of a disruption, which permits the members of a supply chain to respond aptly to disruptive events. This study, hence, aims to uncover the details of how the small and medium-sized enterprises (SMEs) of clothing retailers in Australia build supply chain resilience and what are the major issues experienced by the SMEs while building resilience.

This study is carried out using a descriptive qualitative research design, and data are collected from semi-structured interviews with key informants from managerial levels within the Australian clothing retailers’ businesses.

This study identifies five enablers, namely, collaboration, multi-sourcing, visibility, flexibility and information systems, that the SMEs of clothing retailers mostly consider to achieve resilience in the supply chain. This study also finds that SMEs’ capabilities, cost and financing, lack of managerial autonomy and the inability to create redundancy are the key impediments hindering SMEs from attaining the expected level of resilience.

To the best of the author’s knowledge, this study contributes to the body of knowledge by being one of the first empirical studies to explore the SMEs of clothing retailers’ supply chain resilience in the Australian business context, which can add valuable insights for academics and practitioners in guiding supply chain design decisions for the SMEs in other sectors.

Firms are increasingly pressured to comply with mandatory supply chain transparency (SCT) regulations. Drawing on information processing theory (IPT), this study aims to show how blockchain technology can address information uncertainty and equivocality in assuring regulatory compliance in an interorganizational network (ION).

IPT is applied in a single case study of an ION in the mining industry that aimed to implement blockchain to address mandatory SCT regulations. The authors build on a rich proprietary data set consisting of interviews and substantial secondary material from actors along the supply chain.

The case shows that blockchain creates equality between actors, enables compliance and enhances efficiency in an ION, reducing information uncertainty and equivocality arising from conflict minerals regulation. The system promotes engagement and data sharing between parties while protecting commercial sensitive information. The lack of central authority prevents larger partners from taking control. The system provides mineral provenance and a regulation-compliant record. System cost analysis shows that the system is efficient as it is inexpensive relative to volumes and values of metals transacted. Issues were identified related to collecting richer human rights data for assurance and compliance with due diligence regulations.

The authors provide some of the first evidence in the operations and supply chain management literature of the specific architecture, costs and limitations of using blockchain for SCT. Using an IPT lens in an ION setting, the authors demonstrate how blockchain-based systems can address two key IPT challenges: environmental uncertainty and equivocality.

The home page design of a digital news website is a key factor in determining its attractiveness to readers. This study aims to propose an approach to manage the frequent adjustment of the dynamic layout of the news content on the website home page in a real-time environment to increase its attractiveness to readers.

This paper shows that this news website layout design problem can be modeled as an optimization problem based on the information of news contents that change within a multiple-period planning horizon similar to the dynamic facility layout problem. A hybrid genetic algorithm-based approach integrated with local search heuristic methods is also proposed to improve the solution.

This paper finds that the DPLP model is effective in modeling the changing layout of a digital news website. The problem can solved in a timely manner using the proposed hybrid genetic algorithm.

This paper was based on hypothetical data and on the assumption of equal section size. Actual data would help fine-tune the application of the dynamic facility layout model. As well the algorithm could be enhanced for unequal size sections.

The model should help online newspapers apply sophisticated algorithms to optimize the layout of news websites dynamically in a timely manner.

News websites are increasingly the desired medium to consume news. So it has an important role in educating society. Thus optimizing and improving the process will help in this regard.

To the best of the authors’ knowledge, this paper is the first one to apply the DPLP model to the digital newspaper website dynamic design problem.

The Agenda 2030 have drawn a lot of interest in academic studies. This necessitates accounting research on nonfinancial reporting and sustainable development goals (SDG) disclosure in an under-investigated context. The purpose of this study is to examine the contribution of nonfinancial reporting practices to SDG disclosure by 120 companies from 12 African nations for the years 2016 to 2020.

The study uses a content analysis to gauge how much information are disclosed on SDG by the selected firms. The authors carried out content analysis using the global reporting initiative frameworks to determine the level of SDG disclosure across the companies by examining the selected nonfinancial reports.

Sustainability reports account for 50% of such SDG disclosure making it the highest. This is followed by corporate social responsibility report which accounts for 23%, while environmental reports account for 20% and Chairman’s statement accounts for 7%. The result is expected since corporate sustainability report has been the major channel for disclosing activities relating to social and governance issues in recent times.

The results of this study demand that corporate entities in Africa take responsibility for their actions and exert significant effort to achieve the SDG. While the government has the main responsibility, corporate entities must support the SDG to be realized.

To the best of the authors’ knowledge, this study is one of the few studies that examines nonfinancial reporting practices with a focus on SDG disclosure. In addition, this study offers novel insight into how accounting research contributes to nonfinancial reporting practices and SDG disclosure.

Online reviews serve as valuable sources of information, reflecting tourists’ attentions, preferences and sentiments. However, although the existing research has demonstrated that incorporating online review data can enhance the performance of tourism demand forecasting models, the reliability of online review data and consumers’ decision-making process have not been given adequate attention. To address the aforementioned problem, the purpose of this study is to forecast tourism demand using online review data derived from the analysis of review helpfulness.

The authors propose a novel “identification-first, forecasting-second” framework. This framework prioritizes the identification of helpful reviews through a comprehensive analysis of review helpfulness, followed by the integration of helpful online review data into the forecasting system. Using the SARIMAX model with helpful online review data sourced from TripAdvisor, this study forecasts tourist arrivals in Hong Kong during the period from August 2012 to June 2019. The SNAÏVE/SARIMA model was used as the benchmark model. Additionally, artificial intelligence models including long short-term memory, back propagation neural network, extreme learning machine and random forest models were used to assess the robustness of the results.

The results demonstrate that online review data are subject to noise and bias, which can adversely affect the accuracy of predictions when used directly. However, by identifying helpful online reviews beforehand and incorporating them into the forecasting process, a notable enhancement in predictive performance can be realized.

First, to the best of the authors’ knowledge, this study is one of the first to focus on the data issue of online reviews on tourism arrivals forecasting. Second, this study pioneers the integration of the consumer decision-making process into the domain of tourism demand forecasting, marking one of the earliest endeavors in this area. Third, this study makes a novel attempt to identify helpful online reviews based on reviews helpfulness analysis.