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This chapter introduces the specifics of spirituality-centric management practices in service and operation focused industries. Strategic management practices are often challenged by the human factor of businesses. Consequently, businesses often waver with the fulfillment of their strategic goals and face harmful repercussions. Subsequently, strategic leadership plays a crucial role in the advancement of incorporating spirituality in the workplace and cultivating a perception of the spiritual domain at the individual, team, and organizational levels. To succeed, organizations need to overcome the challenges pertaining their members' retainment and wellness. This is because members often act on their emotional, moral, and ethical concerns that are pillared by their spirituality-centric views on colleagues and management. As the overarching term, workplace spirituality has been linked with organizational learning, togetherness, sense of nurturement, and interpersonal fulfillment with tasks and often coincidences with managerial application of strategic approaches. For the synthesis of service focused businesses, authors exemplify studies within tourism and hospitality industries.

The health of an economy is heavily dependent on the productivity of the economy's major industries including construction. While most macro-measures of productivity in the USA construction industry indicate a decline, corresponding studies at the individual task level indicate an increase in productivity. Therefore, this paper aims to identify areas where productivity challenges exist and thus provide recommendations for improvement in the construction industry.

A model that relates the way construction projects are executed with the sources of data that inform productivity analyses is developed and presented. This effort/value-flow model informs the data analysis that is performed to determine productivity trends for management and field labor. Further analysis for field labor productivity using field data and management productivity was separately conducted. Management productivity was particularly difficult to gauge, resulting in the use of surrogate measures.

It was observed that while both field labor and management productivities at the industry level have been decreasing, the decrease in management productivity was five times that of field labor productivity. A similar trend was observed for management productivity at the project level.

The primary contribution of this paper to the body of knowledge and industry is the introduction of a holistic analysis of USA construction productivity. Recommendations to improve management productivity include the use of technology, especially project management software.

Adapting to external and internal transformations is a difficult task that managers and scholars must face while attempting to keep their organisations alive and well-established. This chapter explores the various decision-making tools that can assist practitioners and scholars to improve their understanding of the external scenario to determine the contemporary appropriateness of these approaches for analysing the environment and their implications for various types of organisations. The chapter investigates the barriers and drivers of these methods and proposes existing alternative paradigms created by academics and practitioners to analyse and comprehend the context. It demonstrates how these decision-making tools can be implemented by providing examples and case studies.

Turnover in high-tech companies has long been a concern for managers and executives. Recent meta-analyses from the general turnover literature consistently show that job satisfaction is a major attitudinal antecedent to turnover intention and turnover behavior. Additionally, the available research on information technology (IT) employees focuses primarily on turnover intentions and not on a risky decision-making perspective and actual turnover (turnover behavior). The paper aim is to focus on that.

This study uses hierarchical ordinary least squares, process (Preacher and Hayes, 2004) and logistic regression.

The main predictor of actual turnover is risky decision-making, whereas job satisfaction is the main predictor of turnover intention.

The joint effects of risk and job satisfaction on turnover intention and behavior have not been studied in the IT domain. Hence, this study extends our understanding of turnover in general and particularly among IT employees by studying the combined effect of risk and job satisfaction on turnover intentions and turnover behavior. The study’s theoretical and practical implications are likewise discussed.

This chapter aims to verify predictors of marital quality in Croatia. As a theoretical starting point, the Huston Socio-ecological model was used. Huston’s so-called “wide-angle and close range” variables were included in to study as predictors of marital quality. A two-level hypothetical model was created consisting of Six groups of predictor variables: Level 1 predictors included Partners’ demographic variables, Partners’ personality, Partners’ value system, Marital processes or dynamics, and Partners’ wellbeing. Level 2 predictors included four Marriage characteristics. Altogether at both levels, 42 variables represented predictors. Marital quality in the marriage was a dependent variable. Eight hundred and eighty-four marital couples from 14 counties in various parts of Croatia and from Zagreb, the country’s capital, were included in the study. Factor analysis, Maximum likelihood with Promax rotation was used to extract factors. Eight factors were extracted: Marital harmony, Distress, Partners’ personality, Negative spillover from work, Traditionalism, Engagement in child care, Participation in decision-making, and Economic hardship. Multilevel analysis using the Mix model in Statistical Package for Social scientist, version 20 was used in data analysis. Predictive on Marital quality in a marriage turned out variables: Marital harmony, Distress, Partners’ personality, Traditionalism, Engagement in child care, and Participation in decision-making as level 1 and Marriage duration (Marriage stages) as a level 2 variable. Huston’s Ecological model proved to be adequate and useful in explaining marital quality.

The purpose of this paper is to propose a decision support framework that can be used by decision-makers to identify the most convenient disruption analysis (DA) methods for megaprojects and their stakeholders.

The framework was initially developed by conducting a comprehensive literature review to obtain extensive knowledge about disruption management and megaprojects. Focus group discussion (FGD) sessions with the participation of the construction practitioners were then organized to validate and strengthen the findings of the literature review. Consequently, 17 selection factors were identified and categorized as requirement, ability and outcome. Lastly, the most convenient DA methods for megaprojects were identified by performing integrated fuzzy analytical hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) analysis. Additionally, consistency analysis was also conducted to verify the reliability of the results.

The results revealed that the measured mile method is the most appropriate DA method for megaprojects. In case the measured mile method cannot be adopted due to various technical and contractual reasons, the decision-makers are proposed to consider program analysis, work or trade sampling, earned value analysis and control chart method, respectively. Second, the selection factors such as “Comprehensible analysis procedure,” “Existing knowledge and experience about a particular DA method,” “Ability to resolve greater number of disruption events,” “Ability to resolve complex disruption events,” “Ability to exclude factors that are not under the owner's responsibility” and “General acceptance by practitioners, courts, and arbitration, etc.” were given the top priority by the experts, highlighting the critical aspects of the DA methods.

Disruption claims in megaprojects are very critical for the contractors to compensate for the losses stemming from disruption events. Although the effective use of DA methods maximizes the accuracy and reliability of disruption claims, decision-makers can barely implement these methods adequately since past studies neglect to present extensive knowledge about the most convenient DA methods for megaprojects. Thus, developing a decision support framework for the selection of DA methods, this study is the earliest attempt that examines the mechanisms and inherent differences of DA methods. Additionally, owing to the robustness and versatility of this research approach, the research approach could be replicated also for future studies focusing on other project-based industries since disruption is also a challenging issue for many other industries.

Purpose: Entrepreneurship is one of the best ways towards self-sufficiency and poverty alleviation for women in a country without guaranteed employment. The research contributes and provides reasons for supporting women’s entrepreneurship, as although it is well-documented that women’s entrepreneurship increases economic growth, other approaches need attention, especially those related to sustainability.

Need for the study: Women have superior emotional intelligence, resilience, and capacity to maintain a healthy work–life balance; women make better business and entrepreneurial leaders. Many businesses see encouraging women to join the workforce as a key to achieving sustainability goals. This study will provide valuable insights into the role of female entrepreneurs in driving sustainable business practices in the USA and India – rural India and urban India.

Methodology: The chapter adopts a descriptive research design methodology in conducting a thorough literature review on the evolution of women entrepreneurship in India. The case-based approach has been adopted to depict women entrepreneurs and their growth stories. The analysis is based on qualitative analysis of secondary data and primary data. This research proposes exciting revelations regarding the trend of women entrepreneurship in India and, from a global perspective, challenges women entrepreneurs face in organised and unorganised sectors in India and policies in different countries that promote women entrepreneurship towards sustainability.

Findings: Women business owners in India help the economy thrive, reduce poverty, and have a greater chance of shaping India’s destiny. This chapter looks at how entrepreneurial actions affect cultural morals and values. Women’s business growth rates vary from country to country, and this variation is influenced by the fact that countries can be broadly categorised as either developed or developing.

This study aims to focus on exploring the construction productivity of building projects under the influence of potential factors. The three primary purposes are (1) determining critical factors affecting construction productivity; (2) identifying causal relationship and occurrence probability of these factors to develop a Bayesian network (BN) model; and (3) validating the accuracy of predictions from the proposed BN model via a case study.

A conceptual framework that includes three performance stages was used. Twenty-two possible factors were screened from a comprehensive literature review and evaluated through expert opinions. Data were collected using a structured questionnaire-based survey and case-study-based survey. The sampling methods were based on non-probability sampling.

Worker characteristic-related factors significantly affect labour productivity for a construction task. Construction productivity is dominated by the working frequency of workers (overtime), complexity of the task, level of technology application and accidents. Labour productivity is defined as nearly 50% of the baseline productivity using the BN model created by the caut 2sal relationship and probability of factors. The prediction error of the BN model was 6.6%, 10.0% and 9.3% for formwork (m²/h), reinforcing steel (ton/h) and concrete (m³/h), respectively.

The evaluation or prediction of productivity performance has become a necessary topic for research and practice.

Managers and practitioners in the construction sector can utilise the outcome of this study to create good productivity management policies for their prospective projects.

Worker-related characteristics are dominant among critical factors affecting labour productivity for a construction task; the proposed BN-based predictive model is built based on these critical factors. The BN approach is highly accurate for construction productivity prediction. The findings of this study can fill gaps in the construction management body of knowledge when modelling construction productivity under the effects of multiple factors and using a simple probabilistic graphic tool.

The purpose of this study is use a bibliometric analysis to explore the relational nature of knowledge creation in WFM in operations. Companies live under constant pressure to find the best ways to plan their workforce, and the workforce emangement (WFM) is one of the biggest challenges faced by managers. Relevant research on WFM in operations has been published in a several range of journals that vary in their scope and readership, and thus the academic contribution to the topic remains largely fragmented.

To address this gap, this review aims to map research on WFM in operations to understand where it comes from and where it is going and, therefore, provides opportunities for future work. This study combined two bibliometric approaches with manual document coding to examine the literature corpus of WFM in operations to draw a holistic picture of its different aspects.

Content and thematic analysis of the seminal studies resulted in the extraction of three key research themes: workforce cross-training, planning workforce mixed methods and individual workforce characteristics. The findings of this study further highlight the gaps in the WFM in operations literature and raise some research questions that warrant further academic investigation in the future.

Likewise, this study has important implications for practitioners who are likely to benefit from a holistic understanding of the different aspects of WFM in operations.