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This chapter deals with the specific principles and issues of the modelling and simulation of hospitality processes. The methodology of hospitality processes modelling is described, and the set of modelled business processes is presented. This chapter shows the selected opportunities and threats of Business Processes Management approach in the hospitality industry. The second part of this chapter is focussed on the business processes simulation as the method of hospitality managers training. The basic proposal of the hotel business processes simulator is presented. The simulated processes structure–monitored KPIs and the simulator functionality are shown as the part of the hotel simulator design to be discussed before the implementation phase of the project.

The purpose of this study was to identify and determine the best fit model of triple bottom line (TBL) performance. Particularly, it delved into the interrelationships among variables which include sustainable management practices, strategic orientation and organizational culture on TBL performance. This study employed descriptive-correlation technique using Structural Equation Modeling. Data were sourced by administering survey questionnaires to 400 individuals performing key functions among large manufacturing companies operating in Region XII, Philippines. Results displayed that sustainable management practices, strategic orientation and organizational culture positively and significantly correlated with TBL performance. Structural Model 4, which depicted the direct causal relationships of sustainable management practices and organizational culture to TBL performance of large manufacturing companies, satisfied all the indices used and was found to be the best fit model. Finally, this study adds value to a growing body of literature viewing TBL through the lens of corporate sustainability.

This chapter uses multiple research methods, including quantitative science mapping analysis (SciMat) and a qualitative literature review, to provide insight into the academic debate unfolding at the intersection of big data and business processes. SciMat analysis based on keyword co-occurrence enabled identifying 12 of the most productive research themes, as reflected in a poll of 301 articles about big data and business processes. The three most important themes are: firm performance, Industry 4.0, and innovation. The traditional literature review on firm performance indicated that big data analytics (BDA) positively influence business process performance and have a beneficial impact on a firm’s performance, that is, the role of big data is viewed as critical in the context of Industry 4.0 because it enhances productivity and improves business processes. The benefits of BDA can be achieved only if the organizational obstacles related to planning, workforce attitude, and alignment with strategy are overcome. Moreover, big data is perceived as a significant source of innovation in an organization and can be conceptualized with the use of a resource-based view (RBV) of the firm. BDA positively influence business processes, which is strengthened by adequate implementation and openness to innovation.

This final chapter delves into the future of digital supply chain management (DSCM) amid today's dynamic business environment, shaped by technological advancements and factors like automation, artificial intelligence (AI), sustainability, and resilience. It emphasizes the crucial role of digital technologies (DTs) such as AI, the Internet of Things (IoT), Industrial IoT, and the Internet of Everything (IoET), along with blockchain, in revolutionizing supply chain operations. These technologies enable agility, flexibility, efficiency, and responsiveness, crucial for supply chains to proactively adapt to market changes. The chapter explores the trends in DSCs, focusing on real-time data analytics, end-to-end visibility, sustainability, and resilience. It highlights the growing importance of transparency in supply chains, driven by consumer demand for sustainable practices and product origins. DSCM is identified as pivotal for prioritizing sustainability, leading organizations toward green practices. Despite the opportunities in DSCM, challenges like cybersecurity, data management complexities, geopolitical uncertainties, and talent shortages are acknowledged. To overcome these, the chapter stresses strategic foresight in DSCM and the importance of robust process management, risk management, and talent development. The future-readiness of supply chain professionals is discussed, highlighting the need for change management, development of social and deep work skills, collaboration, and ethical practices. The chapter concludes by underscoring the transformative potential of DTs in the digital era, urging organizations to embrace innovation, transparency, and sustainability in their supply chains, recognizing that the future of DSC is an imminent reality.