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Nowadays, product and service design play a crucial role in people’s daily life and marketing settings; however, both of the product and service design process have always been affected by various factors, including the growth of technology, economic tensions and endemic and pandemic health challenges. Undoubtedly, the importance of service and product design is increasing in the near future, and these changes are also associated with customers' experience. In this regard, some factors have a prominent place such as customer preferences, marketing improvement, technology push-marketing pull and different aspects of sustainability. Since the development of product–service systems (PSSs) should be based on the requirements and needs of users on the one hand, and environmental and technological considerations on the other hand, the role of product and service designers in the context of presenting creative and innovative ideas is important. The mentioned features are known as the main pillars of industrial design. Industrial design as an integrated science of art and technology concerns customers' experience, user experience (UX) design, innovative design, customer-oriented service development and so on. Industrial design make value not only for customers but also for producers. Besides, some new designscape may develop by industrial design considerations. In this chapter, authors explain the industrial design scope towards customer experience orientation in service design, enhance the experiencescape, design thinking (DT), PSS approaches and sustainability.

While existing research has predominantly focused on the positive relationships between service quality and outcome variables, there has been limited investigation into the influence of food service quality on these variables or the moderating role of stadium atmosphere in the realm of sports marketing. This study aims to fill these gaps by examining the structural relationships between baseball stadium food quality, timeliness, satisfaction, and behavioral intention with an emphasis on the moderating effect of stadium atmosphere.

The data were collected from spectators attending baseball games. This study established the validity of the measurement scale through confirmatory factor analysis, factor loadings, average variance extracted, and construct reliability using Cronbach’s alpha. In addition, this study employed structural equation modeling with maximum likelihood estimation to examine positive relationships and mediating effects and used Jamovi statistical software to conduct moderation analysis.

The findings demonstrate the significant impacts of food quality on satisfaction and behavioral intention, the positive effects of timeliness on satisfaction and behavioral intention, and the notable influence of satisfaction on behavioral intention. Additionally, this study found that satisfaction partially mediates the aforementioned relationships and that stadium atmosphere moderates these pathways.

This study contributes to the literature by addressing the impact of food service quality on outcome variables within sports marketing, an area that has received limited attention. Specifically, it examines how food quality and timeliness influence consumer satisfaction and behavioral intention. Furthermore, the study highlights the moderating role of stadium atmosphere, demonstrating its potential to enhance the relationship between food quality and consumer outcomes. These findings expand our understanding of consumer behavior in sports settings, offering practical strategies for team officials to enhance fan experiences. By diversifying menu options, optimizing concession operations, and collaborating with local vendors, team officials can significantly improve food service quality and create a more engaging stadium atmosphere.

This study aims to investigate the impact of service quality (SQ), perceived value (PV) and consumer satisfaction on Thai street food, with customer satisfaction (CS) as a mediator for customer loyalty and repurchase intention (RI). It also explores how consumer trust (CT) in Thai street food safety moderates these relationships.

Structural equation modelling (SEM) was utilised to analyse the complex interrelationships between various constructs. Multi-group analyses were conducted to investigate the moderating effects of CT on the structural model, considering two distinct groups based on trust levels: low and high.

The findings revealed that SQ and PV significantly influenced CS and behavioural intention, while the perceived quality of Thai street food had no significant impact on post-COVID-19 consumer satisfaction. The study highlighted the critical role of CT in moderating the relationships between SQ, PV and CS, with distinct effects observed in groups with varying trust levels.

The research emphasises the importance of enhancing SQ and delivering value to customers in the context of Thai street food, which can contribute to increased CS, RI and positive word-of-mouth. Furthermore, the study underscores the critical role of building CT in fostering enduring customer relationships and promoting consumer satisfaction and loyalty.

This research offers valuable insights into consumer behaviour and decision-making processes, particularly within the realm of Thai street food. It underscores the significance of understanding and nurturing CT, especially in the post-COVID-19 landscape, emphasising the need for effective business strategies and consumer engagement.

In today’s intricate and dynamic construction sector, traditional project management techniques, which view projects in isolation, are no longer sufficient. Project Portfolio Management (PPM) has proven to be an efficient alternative solution for handling multiple construction projects. As such, based on a Machine Learning (ML) approach, this study aims to explore the Critical Success Factors (CSFs) influencing the adoption of PPM, aiming to enhance PPM implementation in construction projects.

A questionnaire based on CSFs gathered from prior studies was developed and validated by experts. Afterward, exploratory data analysis is conducted to understand CSF–PPM relationships. Preprocessing techniques ensure uniformity in variable magnitudes. Lastly, ML techniques, namely Linear Discriminant Analysis (LDA), Logistic Regression (LR) and Extra Trees Classifier (ETC) are developed to model and investigate CSFs' impact on PPM adoption.

The findings pointed out that the ETC model marginally outperforms other ML models with a classification accuracy of 93%. Also, the project size, utilized PPM tool and resource allocation-related factors are the most significant CSFs that influenced the PPM performance by about 48.5%.

This study contributes to the existing body of knowledge by raising awareness among construction companies and other project stakeholders about the pivotal CSFs that must be considered when prioritizing projects and designing an optimal PPM approach.

The expansion of online shopping aligned with challenging economic conditions has contributed to increasing fraudulent retail product returns. Retailers employ numerous interventions typically determined by embedded perspectives within the company (supply side) rather than consumer-based assessments of their effectiveness (demand side). This study aims to understand how customers evaluate counter-fraud measures on opportunistic returns fraud in the UK. Based on the fraud triangle and the theory of planned behaviour, we develop an empirically informed framework to assist retail practice.

We collected 485 valid survey responses about consumer attitudes regarding which interventions are effective against different types of returns fraud. First, a principal component section evaluates the policies' effectiveness to identify any policy grouping that could help prioritise specific sets of policies. Second, cluster analysis follows a two-stage approach, where cluster size is determined, and then survey respondents are partitioned into subgroups based on how similar their beliefs are regarding the effectiveness of anti-fraud policies.

We identify policies relating to perceived effectiveness of interventions and create customer profiles to assist retailers in conceptualising potential opportunistic fraudsters. Our product returns fraud framework adopts a consumer perspective to capture the perceived behavioural control of potential fraudsters. Results suggest effectiveness of different types of interventions vary between different types of consumers, which leads to the development of propositions to combat the fraud.

This study is unique in assessing the perceived effectiveness of a range of interventions based on data collection and advanced analytics to combat fraudulent product returns in omnichannel retail.