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With the emergence of digital twins, the construction industry is looking toward improving the inspection and maintenance of all kinds of assets, such as bridges, roads and utilities. The purpose of this paper is to provide insights into how the development of an interactive digital twin creates a variety of interactions between users of this technology and assets to be monitored.

The development of a digital twin inspection model, focusing on the specific case of a sewage pumping station, is chosen as the subject of a case study. Through the development of this model, this study explores the various user–technology interactions that can be designed in a digital twin context.

Users interact with digital twins by following virtual instructions in a certain way, which creates a “quasi-other” relationship. A digital twin based on virtual reality (VR) also make users feel as if they are within the created VR of an inspection site, thereby immersing them in the VR environment. The design of a VR-based digital twin, which is determined by decisions made during the development process, shapes the context in which users interact with the technology and assets.

This study shows that a digital twin in construction practice may play different “actant” roles having different types of influences. Analyzing these actant roles and influences in terms of force and visibility adds a new perspective on the interaction between users and digital twins in construction and asset monitoring practice.

Using real-time support systems may help operators in road construction to improve paving and compaction operations. Nowadays, these systems transform from descriptive to prescriptive systems. Prescriptive or operator guidance systems propose operators actionable compaction strategies and guidance, based on the data collected. It is investigated how these systems mediate the perceptions and actions of operators in road pavement practice.

A case study is conducted on the specific application of an operator guidance system in a road pavement project. In this case study, comprehensive information is presented regarding the process of converting input in the form of data from cameras and sensors into useful output. The ways in which the operator guidance systems translate data into actionable guidance for operators are analyzed from the technological mediation perspective.

Operator guidance systems mediate actions of operators physically, cognitively and contextually. These different types of action mediation are related to preconditions for successful implementation and use of these systems. Coercive interventions only succeed if there is widespread agreement among the operators. Persuasive interventions are most effective when collective and individual interests align. Contextual influence relates to designs of the operator guidance systems that determine human-technology interactions when using them.

This is the first study that analyzes the functioning of an operator guidance system using the technological mediation approach. It adds a new perspective on the interaction between this system and its users in road pavement practice.

The research aims to applying Baumol’s framework to address some research gaps in the literature. This paper aims to analyze how institutional variations at the subnational level impact entrepreneurship decisions and the path toward productive or unproductive entrepreneurship in an institutionally underdeveloped country. The results offer potentially new theoretical insights and practical implications for developing or emergent countries.

The research applies Baumol’s framework to Mexico’s context. The research collects data compounded by individual- and state-level variables from diverse sources for the 32 Mexican states. The individual level and some controls were obtained from sources of regular frequency, but the institutional variables were derived from surveys of irregular frequency, nonsynchronic and mostly nonoverlapping, which required aligning and centered them around 2016 and 2019 to match with the individual variables. The authors apply multilevel nonlinear mixed-effects probit regression to test nine hypotheses regarding the impact of institutional variables on entrepreneurial decisions and the path toward productive or unproductive entrepreneurship.

Improved formal institutions across the Mexican states reduce the entrepreneurship probability, implying interactions with other variables and indirect effects; encourage the selection of productive entrepreneurship, e.g. formal ventures; and discourage self-employment. Consequently, those institutions do not encourage entrepreneurship selection as an occupation but entrepreneurial quality, i.e. the selection of productive-formal entrepreneurship and larger ventures. Deficient informal institutions increase the entrepreneurship and formal entrepreneurship probabilities, implying the interactions with other variables and indirect effects and supporting the corruption “greases the wheels” hypothesis, consequently encouraging productive ventures. New evidence of the positive relationship between criminality and entrepreneurship types in Mexico is reported.

Our findings indicate important impacts of the individual-level variables on the entrepreneurship decisions and that most of those decisions are potentially necessity driven and a minority are driven by opportunity, given their relationship with the macroeconomic controls and the institutional variables. The authors report mixed results on the relationship between institutions and entrepreneurship partially consistent with the literature; some results contribute additional evidence on controversial hypotheses or imply the existence of indirect effects. Overall, the results suggest that institutions impact the individual decisions to venture and the type of venture consequently affecting the amount and quality of entrepreneurship across states.

The research addresses some of the literature gaps by providing empirical evidence on a middle-income country and how diverging regional institutional contexts, including formal and informal institutions, impact the individual’s entrepreneurship decisions within an institutionally underdeveloped country. The paper contributes new knowledge and insights into entrepreneurship in emerging or developing countries with implications for Baumol’s framework in this context and adds to the debated hypothesis on the relationship between some institutions, e.g. corruption and criminality and entrepreneurship.

In this article, we reflect on how smart technology is transforming service research discourses about service innovation and value co-creation. We adopt the concept of technology smartness’ to refer to the ability of technology to sense, adapt and learn from interactions. Accordingly, we seek to address how smart technologies (i.e. cognitive and distributed technology) can be powerful resources, capable of innovating in relation to actors’ agency, the structure of the service ecosystem and value co-creation practices.

This conceptual article integrates evidence from the existing theories with illustrative examples to advance research on service innovation and value co-creation.

Through the performative utterances of new tech words, such as onlife and materiality, this article identifies the emergence of innovative forms of agency and structure. Onlife agency entails automated, relational and performative forms, which provide for new decision-making capabilities and expanded opportunities to co-create value. Phygital materiality pertains to new structural features, comprised of new resources and contexts that have distinctive intelligence, autonomy and performativity. The dialectic between onlife agency and phygital materiality (structure) lies in the agencement of smart tech–enabled value co-creation practices based on the notion of becoming that involves not only resources but also actors and contexts.

This paper proposes a novel conceptual framework that advances a tech-based ecology for service ecosystems, in which value co-creation is enacted by the smartness of technology, which emerges through systemic and performative intra-actions between actors (onlife agency), resources and contexts (phygital materiality and structure).

This paper aims to examine whether the audit committee moderates the relationship between audit quality and market reactions.

Using fixed effects and the GMM model for robustness, the study used 472 publicly listed firms on South Africa’s Johannesburg stock exchange spanning a period of six years from 2014 to 2019.

Results obtained show that audit quality impacts market reactions through share price and adjusted market returns. And, that the audit committee moderates the relationship between audit quality and market reactions in South Africa’s publicly listed firms. An effective audit committee is expected to play a crucial role in overseeing the audit process, ensuring the independence of auditors and promoting transparency and accountability which in turn impacts asset prices.

The study implies that governments and regulatory bodies in other developing economies could strengthen regulations about companies’ Acts, how firms regulate themselves and more so audit committees. Firms can also strive to make sure that audit committees are staffed with experts to promote higher audit quality and investor attention to get access to the much-alluded capital.

To the best of the authors’ knowledge, the study adds value by being the first to explore the subject matter of the importance of audit committees in defining audit quality and market reactions in publicly listed firms. The research adds to the body of knowledge on corporate governance and audit quality. It provides a case study specific to the South African context, contributing to the global literature on these topics.

The increased utilization of artificial intelligence-enabled applications (AI-ETs) across the customer journey has transformed customer experience (CX), introducing entirely new forms of the concept. This paper aims to explore existing academic research on the AI-enabled customer experience (AICX), identifying gaps in literature and opportunities for future research in this domain.

A systematic literature review (SLR) was conducted in March 2022. Using 16 different keyword combinations, literature search was carried across five databases, where 98 articles were included and analysed. Descriptive analysis that made use of the Theory, Characteristics, Context, Methods (TCCM) framework was followed by content analysis.

This study provides an overview of available literature on the AICX, develops a typology for classifying the identified AI-ETs, identifies gaps in literature and puts forward opportunities for future research under five key emerging themes: definition and dynamics; implementation; outcomes and measurement; consumer perspectives; and contextual lenses.

This study establishes a fresh perspective on the interplay between AI and CX, introducing the AICX as a novel form of the experience construct. It also presents the AI-ETs as an integrated and holistic unit capturing the full range of AI technologies. Remarkably, it represents a pioneering review exclusively concentrating on the customer-facing dimension of AI applications.

随着人工智能应用程序 (AI-ET)在旅途中的使用不断增加, 消费者体验 (CX)得以转变, 引入了全新的概念形式。 本文旨在探索有关人工智能客户体验（AICX）的现有学术研究, 从中找出文献中的空白以及该领域未来研究的机会。

本系统性文献综述（SLR）于2022 年 3 月开工。基于16 个不同的关键词组合, 本综述统共收录并分析了来自 5 个数据库98 篇文献, 采用理论-特征-背景-方法 (TCCM) 框架先后进行描述性分析和内容分析。

该研究概述了 AICX 的现有文献, 开发了对已识别的 AI-ET 进行分类的类型学, 确定了现有文献中的空白, 并在 5 个关键新兴主题下提出了未来研究的机会：1. 定义和动态, 2 . 实施, 3. 结果和衡量, 4. 消费者视角, 5. 情境视角。

本研究建立了全新的视角看待 AI 和 CX 之间的相互作用, 引入了 AICX 这种新颖的体验构造形式, 还将 AI-ET 展示为一个集成了全方位人工智能技术的整体单元。 值得一提的是, 本文代表了一项专门关注人工智能应用面向客户维度的开创性综述。

La creciente utilización de aplicaciones habilitadas por inteligencia artificial (AI-ET) a lo largo del recorrido del cliente han transformado la experiencia del cliente (CX), introduciendo formas totalmente nuevas del concepto. Este artículo pretende explorar la investigación académica existente sobre la experiencia del cliente a través de la IA (AICX), identificando las lagunas en la literatura y las oportunidades para futuras investigaciones en este ámbito.

En marzo de 2022 se llevó a cabo una revisión bibliográfica sistemática (SLR). Utilizando 16 combinaciones diferentes de palabras clave, se realizó una búsqueda bibliográfica en 5 bases de datos en las que se incluyeron y analizaron 98 artículos. El análisis descriptivo que hizo uso del marco Teoría, Características, Contexto, Métodos (TCCM) fue seguido del análisis de contenido.

El estudio ofrece una visión general de la bibliografía disponible sobre la AICX, desarrolla una tipología para clasificar las AICX detectadas, identifica lagunas en la literatura y plantea oportunidades para futuras investigaciones bajo cinco temas emergentes claves: 1. Definición y dinámica, 2. Implementación, 3. Resultados y medición, 4. Perspectivas del consumidor, 5. Lentes contextuales.

El estudio establece una nueva perspectiva sobre la interacción entre la IA y la CX, introduciendo la AICX como una forma novedosa del constructo experiencia. También presenta las AICX como una unidad integrada y holística que capta toda la gama de tecnologías de la IA. Notablemente, representa una revisión pionera que se concentra exclusivamente en la dimensión orientada al cliente de las aplicaciones de la IA.

The purpose of this study is to examine the associations between board size, board independence and triple bottom line (TBL) reporting. The TBL report consists of three components, namely, environmental, social and economic indices.

This study’s sample consists of top 50 listed companies from the year 2017 to 2019 on Tadawul Stock Exchange. Ordinary least squares, quantile least squares and robust least squares are used to investigate the associations between board characteristics and TBL reporting, including its separate components.

The authors find a significant negative association between TBL reporting and board independence. Social bottom line is significantly and negatively related to board size and board independence. Results indicate that board independence negatively influences the TBL disclosure of companies. Therefore, companies are encouraged to embrace TBL reporting. This suggests that businesses should improve the quality of their reporting while ensuring that voluntary disclosures reflect an accurate and fair view in order to preserve a positive relationship with stakeholders.

The present study explains the evidence for the determinants of the TBL in Saudi Arabia.

This study aims to investigate the impact of job rotation on employee performance and explores the mediating role of human resources (HR) strategy and training effectiveness on this relationship, within the petrochemical industry, which represents a highly specialist and hazardous industrial context.

Data was collected through a questionnaire which was distributed among the experts working in an Iranian petrochemical organization. Previously validated scales were used to measure job rotation, employee performance, HR strategy and training effectiveness, and partial least squares structural equation modeling was used for hypothesis testing.

The research findings indicated that job rotation had a negative effect on employee performance, while training effectiveness and HR strategy positively mediated the relationship between job rotation and employee performance. This highlights the importance of ensuring effective training and a HR strategy to support job rotation of skilled and specialist employees.

Managers of employees in specialist and hazardous industries, such as petrochemical workers, interested in job rotation to support employee career development, should be mindful of potential negative implications on employee performance. To support and improve employee performance, job rotation should be considered alongside HR strategy and training.

Previous research has largely focused on the value of job rotation to develop managers’ organizational understanding and to reduce injury within blue-collar work, which has led to a paucity of research into job rotation within highly skilled and specialist industrial roles. It is highlighted within the literature that it remains unclear what supports effective job rotation. This study addresses this lacuna by investigating how job rotation affects employee performance in a highly skilled and specialized industry and how strategy and training effectiveness mediate this effect.

Given the growth of virtual reality (VR)-based tourism experiences in the past five years, this study aims to investigate the impact of VR-based interactions (ergonomics and embodiment) on memorable experiences and revisit intention mediated by cognitive and emotional responses.

This study has used an exploratory sequential mixed methodology research design to operationalise this research. Study 1 uses qualitative in-depth interviews to explore the proposed research questions, and Study 2 uses a 3 × 3 factorial experimental research design to test the proposed hypothetical model with 355 samples.

The results indicate that embodiment plays a more crucial role than VR ergonomics. Also, the cognitive response in the virtual tour indirectly generates a more memorable experience than the emotional response.

This research uses the theory of technological mediation as an overarching framework to conceptualise the research. Also, the research has applied the tenets of cognitive embodiment theory, metacognitive theory and other related theories to develop the arguments. Thus, the results of this research will extend the holistic understanding of these theories.

This research will guide VR tourism developers in understanding the requirements and expectations of tourists. It also serves as a manual to understand how tourists process the VR tour psychologically.

Very minimal focus was given to understanding the tourists’ interaction with technology in VR tours. The concept of ergonomics and embodiment investigated as an experimental variable is a novel approach in technology-based tourism research.

This paper aims to examine and compare the dividend ratios’ statistical and economic ability to predict the equity premium in the UK and US markets and two US sub-indices (S&P 500 Growth and S&P 500 Value).

In this paper, the authors use the linear regression models to examine the dividend ratios’ statistical ability to predict the equity premium. The in-sample and out-of-sample approaches, including Diebold and Mariano (1995) statistics, and Goyal and Welch’s (2003) graphical approach, are used. Also, the mean-variance analysis is used to test the economic significance.

The paper findings indicate that the dividend ratios have in-sample and out-of-sample predictive abilities in both UK and US markets and both US sub-indices. However, the results show that the dividend ratios have a less impressive predictive ability in the US market compared to the UK market and less in the US value index than the US growth index. This could indicate that there is no relation between the number of companies that distribute dividends in each index and the informativeness of dividends ratios. Furthermore, the tests show the dividend ratios’ predictive ability departure during particular periods and in some indices.

Results and implications of this research are exclusively applied to the US and UK markets. These results can also be applied with caution to other markets, taking into consideration the distinctive characteristics of these markets.

Results revealed in this paper imply that the investors in any of the indices may experience economic gain by adopting a dynamic trading strategy using the information content of the dividend ratios prediction models instead of the benchmark model, which is the prevailing simple moving average model.

This paper adds value through testing the prediction models’ economic significance in two well-developed markets, in addition to exploring the relationship between the number of companies distributing cash dividends and the dividends ratio prediction ability. Unlike most of the previous studies in which dividend ratios’ prediction ability is attributed to the number of companies that distribute dividends in the market, this paper denied this interpretation by studying two S&P 500 sub-indices. To the best of the authors’ knowledge, this is the first study to test the prediction models’ ability for these sub-indices.