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Recreational scuba diving is one of the fastest growing tourism industries around the world and has become a popular activity in Taiwan. Few studies focus on enduring involvement with a high risk or difficult activity specialization, so this study aims to explore the causal relationship between enduring involvement and specialization and seeks to explain sustained involvement in scuba diving activity as a recreation specialization.

This research selects four diving sites in Taiwan as survey locations, specifically Yeliou, Longdong, Kenting and Green Island. The questionnaire consists of three sections, including demographic information, enduring involvement and specialization. By analyzing the data collected from 810 scuba divers in Taiwan, structural equation modeling is used to examine the causal relationships among the variables.

The primary findings of this study are as follows: attraction positively affects divers’ commitment and lifestyle through joy, relaxation and sharing diving experiences; the results indicate that self-expression is associated with past experience of participating in scuba diving activity; and centrality indicates that participants’ daily life and recreation are related to each other and become central to their life. Results show that most theoretical hypotheses are supported, but there is no significant evidence of attraction impacting past experience or self-expression influencing commitment and lifestyle.

To the best of the authors’ knowledge, this study is the first to examine the causal influence of enduring involvement and specialization in the scuba diving context. The findings provide a solid theoretical basis for the study of sustained involvement motivation and behavior on specialization. Implications and recommendations for future research are discussed.

休闲水肺潜水是全球发展最快的旅游业之一, 已成为台湾的热门活动。很少有研究关注持续涉入高风险或困难活动的专门化, 因此本研究探讨持续涉入和专门化之间的因果关系, 并试图解释持续参与水肺潜水活动作为休闲专门化。

这项研究选择了台湾的四个潜水地点作为调查地点, 特别是野柳, 龙洞, 垦丁和绿岛。问卷分为三个部分, 包括人口统计信息, 持续参与和专门化。通过分析从台湾810名潜水员那里收集的数据, 使用结构方程模型检查变量之间的因果关系。

这项研究的主要发现是：（1）吸引力通过愉悦, 放松和分享潜水经历积极影响潜水员的承诺和生活方式; （2）结果表明自我表达与过去参加水肺潜水活动的经历有关（3）中心性表示参与者的日常生活和娱乐彼此相关, 并成为他们生活的中心。结果表明, 大多数理论假设均得到支持, 但没有显着证据表明吸引力会影响过去的经历或自我表达影响承诺和生活方式。

据我们所知, 本研究是第一个研究在潜水环境中持续涉入和专门化的因果关系影响的研究。研究结果为专门化持续参与动机和行为的研究提供了坚实的理论基础。 讨论了对未来研究的影响和建议。

El buceo recreativo es una de las industrias turísticas de más rápido crecimiento en todo el mundo y se ha convertido en una actividad popular en Taiwán. Pocos estudios se centran en la participación duradera con una especialización de actividad difícil o de alto riesgo, por lo que este estudio explora la relación causal entre la participación duradera y la especialización y busca explicar la participación sostenida en la actividad de buceo como una especialización recreativa.

Esta investigación selecciona cuatro sitios de buceo en Taiwán como lugares de estudio, específicamente Yeliou, Longdong, Kenting y Green Island. El cuestionario consta de tres secciones, que incluyen información demográfica, participación duradera y especialización. Al analizar los datos recopilados de 810 buzos en Taiwán, se utiliza un modelo de ecuaciones estructurales para examinar las relaciones causales entre las variables.

Los hallazgos principales de este estudio son: (1) la atracción afecta positivamente el compromiso y el estilo de vida de los buceadores a través de la alegría, la relajación y el intercambio de experiencias de buceo, (2) los resultados indican que la autoexpresión está asociada con la experiencia pasada de participar en actividades de buceo., y (3) la centralidad indica que la vida diaria y la recreación de los participantes están relacionadas entre sí y se vuelven centrales en su vida. Los resultados muestran que la mayoría de las hipótesis teóricas están respaldadas, pero no hay evidencia significativa de que la atracción afecte la experiencia pasada o la autoexpresión que influya en el compromiso y el estilo de vida.

Hasta donde sabemos, este estudio es el primero en examinar la influencia causal de la participación y la especialización duraderas en el contexto del buceo. Los hallazgos proporcionan una base teórica sólida para el estudio de la motivación y el comportamiento de participación sostenida en la especialización. Se discuten las implicaciones y recomendaciones para futuras investigaciones.

The challenges facing 21st-century society are becoming increasingly complex, requiring the development of new citizen competencies. This study aims to validate an educational model focused on developing complex thinking in higher education students. Current educational models lack future-ready competencies, necessitating the emergence of new models to guide future generations toward the common good.

This was an adaptation of the causal-layered analysis (CLA) applied to 415 participants from higher education institutions in Mexico, Panama and Spain. Sessions were designed to present the proposed educational model and explore participants’ perceptions of its significance and contributions to future education.

Key findings include the following: participants perceived complexity as difficult and challenging; causes of problems were linked to outdated educational models requiring replacement by those that develop students’ competencies; participants envisioned changes that would develop individuals capable of understanding and transforming society; and participants recognized the model’s transformative potential, offering a novel proposal for 21st-century education.

This research sought to gather opinions from different stakeholders using the CLA methodology, providing a deep understanding of participants’ perspectives on the proposed solution.

In recent decades, emerging market multinational enterprises (EMNEs) have predominantly adopted a big step internationalization strategy to expand their business overseas. This study aims to examine the effect of big step internationalization on the speed of subsequent foreign direct investment (FDI) expansion for EMNEs. The authors also investigate the potential boundary conditions.

The authors use the random effects generalized least squares (GLS) regression following a hierarchical approach to analyze the panel data set conducted by a sample of publicly listed Chinese firms from 2001 to 2012.

The findings indicate that implementing big step internationalization in the initial stages accelerates the speed of subsequent FDI expansion. Notably, the authors find that this effect is more pronounced for firms that opt for acquisitions as the entry mode in their first big step internationalization and possess a board of directors with strong political connections to their home country’s government. In contrast, the board of director’s international experience negatively moderates this effect.

This study provides insights into our scholarly and practical understanding of EMNEs’ big step internationalization and subsequent FDI expansion speed, which offers important implications for firms’ decision-makers and policymakers.

This study extends the internationalization theory, broadens the international business literature on the consequences of big step internationalization and deepens the theoretical and practical understanding of foreign expansion strategies in EMNEs.

This study aims to focus on the five most relevant and discursive emerging technologies in accounting (cloud computing, big data and data analytics, blockchain, artificial intelligence (AI) and robotics process automation [RPA]). It investigates the adoption and use of these technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey.

The study investigates the adoption and use of emerging technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey. This study considers the said nature and characteristics of emerging technologies and proposes a model using the factors that have been found to be significant and most commonly investigated by existing prior technology-organization-environment (TOE)-related technology adoption studies. This survey applies the TOE framework and examines the influence of significant and most commonly known factors on Canadian firms’ intention to adopt the said emerging technologies.

Study results indicate that Canadian accounting professionals’ self-assessed knowledge (about these emerging technologies) is more theoretical than operational. Cloud computing is highly used by Canadian firms, while the use of other technologies, particularly blockchain and RPA, is reportedly low. However, firms’ intention about the future adoption of these technologies seems positive. Study results reveal that only the relative advantage and top management commitment are found to be significant considerations influencing the adoption intention.

Study findings confirm some results presented in earlier studies but provide additional insights from a new perspective, that of accounting professionals in Canada. The first limitation relates to the respondents. Although accounting professionals provided valuable insights, their responses are personal views and do not necessarily represent the views of other professionals within the same firm or the official position of their accounting departments or firms. Therefore, the exclusion of diverse viewpoints from the same firm might have negatively impacted the results of this study. Second, this study sample is limited to Canada-based firms, which means that the study reflects only the situation in that country. Third, considering the research method and the limit on the number of questions the authors could ask, respondents were only asked to rate the impact of these five technologies on the accounting field and to clarify which technologies are used.

This study’s findings confirm that the organizational intention to adopt new technology is not primarily based on the characteristics of the technology. In the case of emerging technology adoption, the decision also depends upon other factors related to the internal organization. Furthermore, although this study found no support for the effect of environmental factors, it fills a gap in the literature by including the factor of vendor support, which has received little attention in prior information technology (IT)/ information system (IS) adoption research. Moreover, in contrast to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.

The study findings may serve as a guide for researchers, practitioners, firms and other stakeholders, particularly technology providers, interested in learning about emerging technologies’ adoption and use in Canada and/or in a relevant context. Contrary to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.

The study provides insights into the said technologies’ actual adoption and improves the awareness of firms and stakeholders to the effect of some constructs that influence the adoption of these emerging technologies in accounting.

This study aims to investigate why and how shared service centres (SSCs) are implemented as well as how they affect audit firm practice and audit quality.

In this qualitative study guided by the theoretical framework of institutional theory, the authors conducted 25 semi-structured interviews in seven European countries, including 16 interviews with audit partners from Big 4 firms, 6 with audit team members, 2 with interviewees from second-tier audit firms and 1 with a member of an oversight body.

The authors show that the central rationale for audit firms to implement SSCs is economic rather than external legitimacy. The authors find that SSC implementation has substantial effects on audit practices, particularly those related to standardisation, coordination and monitoring activities. The authors also highlight the potential impacts on audit quality.

By exploring the motivation for and effects of SSC implementation amongst audit firms, the authors offer insights into the best practices related to subsequent change processes and audit quality.

The purpose of this paper is to analyse and classify the literature that contributed to three questions, namely, what are the benefits of big data analytics (BDA) in the field of supply chain management (SCM) and logistics, what are the challenges in BDA applications in the field of SCM and logistics and what are the determinants of successful applications of BDA in the field of SCM and logistics.

This paper conducts a systematic literature review (SLR) to analyse the findings of 44 selected papers published in the period from 2016 to 2020, in the area of BDA and its impact on SCM. The designed protocol is composed of 14 steps in total, following Tranfeld (2003). The selected research papers are categorized into four themes.

This paper identifies sets of benefits to be gained from the use of BDA in SCM, including benefits in data analytics capabilities, operational efficiency of logistical operations and supply chain/logistics sustainability and agility. It also documents challenges to be addressed in this application, and determinants of successful implementation.

The scope of the paper is limited to the related literature published until the beginning of Corona Virus (COVID) pandemic. Therefore, it does not cover the literature published since the COVID pandemic.

This paper contributes to the academic research by providing a roadmap for future empirical work into this field of study by summarising the findings of the recent work conducted to investigate the uses of BDA in SCM and logistics. Specifically, this paper culminates in a summary of the most relevant benefits, challenges and determinants discussed in recent research. As the field of BDA remains a newly established field with little practical application in SCM and logistics, this paper contributes by highlighting the most important developments in contemporary literature practical applications.

This study examines the mediating roles of the three dimensions of business intelligence (sensing capability, transforming capability and driving capability) in the relationship between the three dimensions of big data analytics capability (big data analytics management, technology and talent capabilities), and radical innovation among Chinese manufacturing enterprises.

A theoretical framework was developed using the resource-based view. The hypothesis was tested using empirical survey data from 326 Chinese manufacturing enterprises.

Empirical results show that, in the Chinese manufacturing context, business intelligence sensing capability, business intelligence transforming capability and business intelligence driving capability positively mediate the impact of big data analytics capability on radical innovation.

The results offer managerial guidance for leaders to properly use big data analytics capability, business intelligence and radical innovation as well as offering theoretical insight for future research in the manufacturing industry’s radical innovation.

This is among the first studies to examine three dimensions of big data analytics capability on the manufacturing industry’s radical innovation by considering the mediating role of three dimensions of business intelligence.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

The literature mainly concentrates on the relationships between externally oriented digital transformation (ExtDT), big data analytics capability (BDAC) and business model innovation (BMI) from an intra-organizational perspective. However, it is acknowledged that the external environment shapes the firm's strategy and affects innovation outcomes. Embracing an external environment perspective, the authors aim to fill this gap. The authors develop and test a moderated mediation model linking ExtDT to BMI. Drawing on the dynamic capabilities view, the authors' model posits that the effect of ExtDT on BMI is mediated by BDAC, while environmental hostility (EH) moderates these relationships.

The authors adopt a quantitative approach based on bootstrapped partial least square-path modeling (PLS-PM) to analyze a sample of 200 Italian data-driven SMEs.

The results highlight that ExtDT and BDAC positively affect BMI. The findings also indicate that ExtDT is an antecedent of BMI that is less disruptive than BDAC. The authors also obtain that ExtDT solely does not lead to BDAC. Interestingly, the effect of BDAC on BMI increases when EH moderates the relationship.

Analyzing the relationships between ExtDT, BDAC and BMI from an external environment perspective is an underexplored area of research. The authors contribute to this topic by evaluating how EH interacts with ExtDT and BDAC toward BMI.