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This chapter will examine two questions. First, how can art and cultural heritage contribute to the health and well-being of a place within the context of the tourism industry? More specifically, can cultural tourism be a driver for community sustainability, that is, not only environmental sustainability but also social empowerment, cultural preservation, and economic vitality? To explore these questions, the author begins by establishing the ways art and environment are closely intertwined, while pondering how cultural production generally – along with the cultural tourists it attracts – can be a driver for sustainability in tourism settings. The benefits that the arts draw from the environment as well as the ways the environment benefits from the arts will be examined. In the next section, the author unpacks how cultural tourism, and more specifically art production, can be drivers for environmental sustainability through social and eco-entrepreneurship and the creation of a shared social value. In the third section, the author identifies some of the challenges inherent in government regulation and preservation of cultural heritage sites. The author argues that communication, cooperation, and relationship building, not just between governing bodies and private stakeholders, but with residents and tourists, should be prioritized in destination management and marketing strategies. In the end, the author proposes that this type of strategy is vital in order to move toward greater cultural, environmental, social, economic, and other kinds of sustainability in the tourism industry.

This article introduces the Responsible AI for Service Excellence (RAISE) framework. RAISE is a strategic framework for responsibly integrating AI into service industries. It emphasizes collaborative AI design and deployment that aligns with the evolving global standards and societal well-being while promoting business success and sustainable development.

This multidisciplinary conceptual article draws upon the United Nations' Sustainable Development Goals (SDGs) and AI ethics guidelines to lay out three principles for practicing RAISE: (1) Embrace AI to serve the greater good, (2) Design and deploy responsible AI and (3) Practice transformative collaboration with different service organizations to implement responsible AI.

By acknowledging the potential risks and challenges associated with AI usage, this article provides practical recommendations for service entities (i.e. service organizations, policymakers, AI developers, customers and researchers) to strengthen their commitment to responsible and sustainable service practices.

This is the first service research article to discuss and provide specific practices for leveraging responsible AI for service excellence.

In this study, the authors investigate if analysts, as knowledgeable information intermediaries, can correctly identify bank corporate social responsibility (CSR) activities and can reliably transmit that information to investors. Hence, the authors specifically explore if analysts perceive and behave differentially in the presence of genuine bank CSR activities (strengths). The authors also analyze if financial markets differentially assess bank CSR strengths. The authors further explore the viability of focusing on analyst and financial markets to validate genuine bank CSR strengths.

The authors use COMPUSTAT and CRSP for firm and financial data, I/B/E/S for analyst reporting data and MCSI Research KLD for CSR data. The sample consists of 329 distinct banks and 2,525 bank-year observations from 2003 to 2016. The primary CSR score is the total number of CSR strengths less the total number of CSR concerns, across six of the seven dimensions for each firm in each year of the sample (Adjusted CSR Score). In addition, the authors estimate all the analyses with dis-aggregated measures of total CSR strengths and total CSR concerns (Adjusted Total Strength Score).

The authors find that analysts correctly distinguish and construe bank CSR strengths from CSR concerns. Specifically, bank CSR strengths increase analyst following and forecast accuracy, while decreasing analyst forecast dispersion. The authors further find that bank CSR strengths increase bank market returns. These results are reversed for bank CSR concerns. Additionally, the authors demonstrate that this method using knowledgeable intermediaries can help validate bank CSR strengths.

The sample is limited to US banks and financial markets. The regulatory and information environment is likely to be different from global or emerging markets. However, since banks in many countries aspire to emulate the US banks, these results would be a precursor of banking sectors conditions in emerging markets. Additionally, the availability of data limits the sample to a period that ends in 2016. To the extent that the importance of ESG and CSR concerns has increased in the intervening time, the results may not accurately reflect the current state of the market.

This investigation benefits researchers, customers, banking executives, regulators and activist groups. First, the authors show that in addition to customers, analysts and the financial markets appreciate bank CSR strengths. Second, despite sophisticated financial reporting by banks, analysts correctly distinguish and construe bank CSR strengths. Third, the authors demonstrate a method for bank marketing researchers to validate genuine bank CSR activity, as well as provide additional support for customer related bank CSR outcomes. Fourth, the findings highlight the importance for banks to have high-quality CSR reporting. This might be especially helpful to a bank rebuilding its reputation after a CSR failure. Finally, this investigation using US banks could serve as a precursor for future bank CSR research and help develop CSR reporting guidelines for banks in emerging economies.

This investigation benefits researchers, customers, banking executives, regulators and activist groups.

This investigation benefits researchers, customers, banking executives, regulators and activist groups. First, the authors show that in addition to customers, analysts and the financial market appreciates bank CSR strengths. Second, despite sophisticated financial reporting by banks, analysts correctly distinguish and construe bank CSR strengths. Third, the authors demonstrate a method for bank marketing researchers to validate genuine bank CSR activity, as well as provide additional support for customer related bank CSR outcomes. Fourth, the findings highlight the importance for banks to have high-quality CSR reporting. This might be especially helpful to a bank rebuilding its reputation after a CSR failure. Finally, this investigation using US banks could serve as a precursor for future bank CSR research and help develop CSR reporting guidelines for banks in emerging economies.

Rebar is the prime component of reinforced concrete structures, and rebar monitoring is a time-consuming and technical job. With the emergence of the fourth industrial revolution, the construction industry practices have evolved toward digitalization. Still, hesitation remains among stakeholders toward the adoption of advanced technologies and one of the significant reasons is the unavailability of knowledge frameworks and implementation guidelines. This study aims to investigate technical factors impacting automated monitoring of rebar for the understanding, confidence gain and effective implementation by construction industry stakeholders.

A structured study pipeline has been adopted, which includes a systematic literature collection, semistructured interviews, pilot survey, questionnaire survey and statistical analyses via merging two techniques, i.e. structural equation modeling and relative importance index.

The achieved model highlights “digital images” and “scanning” as two main categories being adopted for automated rebar monitoring. Moreover, “external influence”, “data-capturing”, “image quality”, and “environment” have been identified as the main factors under “digital images”. On the other hand, “object distance”, “rebar shape”, “occlusion” and “rebar spacing” have been highlighted as the main contributing factors under “scanning”.

The study provides a base guideline for the construction industry stakeholders to gain confidence in automated monitoring of rebar via vision-based technologies and effective implementation of the progress-monitoring processes. This study, via structured data collection, performed qualitative and quantitative analyses to investigate technical factors for effective rebar monitoring via vision-based technologies in the form of a mathematical model.

The purpose of this paper is to identify the areas and logic of integration of different stakeholders using different methods and to analyse their applicability and challenges in practical projects. The main aim is to describe how these different methods impact value creation.

Action design research was carried out in a large hospital construction project where the first author acted as an “involved researcher” and the second author acted as an “outside researcher”. Two workshops were organised to evaluate the direct and indirect challenges and benefits of the applied four methods and to explain how different methods enable value creation.

All the studied methods provide good results in terms of usability and commitment to the aims of the project, thus delivering the direct benefits expected. Process, people and tools logic works well in this case project when applying the methods properly. Significant evidence was provided on secondary deliverables of the methods, and all analysed methods had a significant impact in the area of leading people, clarifying what “focus on people” means and how it is enabled.

Focus on people can be achieved through different operative methods if applied in the right way. It is necessary to select the most suitable methods based on all the direct and indirect deliverables.

This case project offered a platform to analyse integration methods in a real-life project using the collaborative contract method. The authors were able to participate in the analysis by taking action from the very beginning of the project in terms of training, learning, continuous development and coaching of these methods and evaluating the applicability.

Organizations in today's changing environment face significant challenges, requiring continual innovation. Understanding oneself from the employee's perspective is paramount, especially in organizations and businesses, transforming all levels, accommodating new work paradigms and adapting to the post-pandemic business world. The authors examine the employees' critical dimensions, self-concept and resilience through self-reported studies to ascertain the impact on their performance in the organization. Self-concept, a multidimensional knowledge structure, implies the individual's description and examination, including psychological characteristics, attributes and skills. On the other hand, resilience is adapting appropriately to adversity, challenges and stressful situations and emerging unscathed. Resilience additionally leads to profound personal growth and acceptance of reality. It also endows the individual's sense of identity over time. It provides insights into work behavior and outcomes and fosters a positive psychological perspective to improve performance. Job performance is an observable individual performance that adds value and enables organizational goal achievement. To sum job performance is an achievement-related behavior. The research study examines the relationship between employee self-concept, resilience and performance elements (task, contextual and counterproductive work behavior).

Cross-sectional data were collected from 224 employees from the retail sector to test the hypotheses among self-concept, employee performance elements and resilience. SPSS 21.0 was used, and the authors conducted reliability, correlation and regression analysis using statistical tools to analyze the mediating effect.

Self-concept and employee performance elements have significant relationships. The mediating effect of resilience on the relationship between self-concept and counterproductive work behavior and self-concept and contextual performance is significant. In contrast, resilience does not impact the relationship between self-concept and task performance.

The authors examined a framework of untested variables, namely self-concept and the different factors of performance (task, contextual and counterproductive behavior). The authors investigated the mediating effect of resilience in the model, which was not previously explored.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

The current study aims to advance the research on the extra-industry network, innovativeness and performance of small and medium enterprises (SMEs) by examining the mediation role of proactiveness. The study also aims to examine the mediating role innovativeness between extra-industry network and performance.

This study used the proportionate stratified random sampling method to select the study sample and the questionnaire survey approach to 580 SMEs. A total of 150 completed questionnaires were returned. Partial least squares structural equation modeling was administered to analyze data via Smart PLS 3.0 software.

The results reflect that proactiveness is mediated by the relationship between the extra-industry network and the performance of Iranian SMEs. In addition, the results illustrated that proactiveness is mediated by the relationship between innovativeness and the performance. The findings also address the limitation of previous studies on Iranian SMEs through the independent examination of the mediating role of innovativeness between firm extra-industry network and performance.

This article is one of few attempts that have addressed the significance of proactiveness as the key mechanism to transform the advantages of extra-industry network and innovativeness relationships to enhance performance.