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The purpose of this study is to provide information that reflects the true state of affairs and to develop a conceptual model that examines the moderating effect of uncertainty on relative brand trust–love.

Extant empirical studies, conceptual literature and related theories were identified and integrated to develop the conceptual model.

Findings of the study suggest that relative brand trust–love arises because of different components of uncertainty. Relative brand trust–love exhibited by the customer is moderated by uncertainty at the individual level, brand level and technology level. These uncertainties represent the situation that considers if relative brand trust–love can be enhanced. A few propositions have been suggested for such situations to enhance relative brand trust–love.

This paper proposes a conceptual model and also makes research propositions that need to be validated and confirmed empirically. It adds value to theoretical advancements in strengthening the customer–brand relationship. Furthermore, results suggest that relative brand trust–love can be improved over time if these components can be supported by increasing information at different levels. The conclusions will be informative to practitioners and brand managers in strengthening a brand into the market more effectively. Moreover, it can transform the brand into a global brand and help build sustainable long-term relationships. Findings can be useful and interesting information for the researchers who are interested in finding strategic ways for effective decision-making related to brand trust and brand love.

The conceptual model, and the propositions related to different levels of uncertainty, and its effect on relative brand trust–love, is a new approach in enhancing relative brand trust–love and hence helpful in strengthening the quality of customer–brand relationships.

To influence consumer pre-purchase decision-making processes, such as brand selection and perceived brand experience, brands are interested in adopting hyperconnected technological stimuli, such as artificial intelligence, augmented reality (AR), virtual reality, social media and tech devices. However, the understanding of different hyperconnected touchpoints remained shallow and results mixed in previous literature, despite the fact that these touchpoints span different technological interfaces/devices and may influence consumer brand selection. This paper aims to solidify the conceptual underpinnings of the role of online hyperconnected stimuli, which may influence consumer psychological reactions in terms of brand selection and experience.

This paper is conceptual and presents a discussion based on extant literature from various international publishers.

The authors revealed different technological stimuli in the online hyperconnected environment that may influence consumer online hyperconnected brand selection (OHBS), perceived online hyperconnected brand experience (OHBE), perceived well-being and behavioral intention.

The conceptual understanding of OHBS and perceived OHBE was mixed and inconsistent in previous studies. This paper brings together extant literature to establish the conceptual understanding of antecedents and outcomes of OHBS, i.e. perceived OHBE, perceived well-being and behavioral intention, and presents a cohesive conceptual framework.

Crisis response has emerged as a salient concern for firms in the onset of COVID-19. While research suggests that resilience is critical during such disruptions, there remains a need to examine how firms build resilience during evolving situations. This study focuses on resiliency created through operational flexibility and examines how firms developed resiliency to COVID-19 through an adaptation of three technology-based levers of flexibility: change in a firm's product and service offerings, the channel it uses for sales and the location of a firm's workforce.

This study uses a unique cross-sectional dataset generated from a survey administered by a reputable financial institution, from March 20 to June 20, during the inception of COVID crisis. This study uses ordinary least squares to analyze data from 6,076 firms across 20 countries.

Results indicate that flexibility through a combination of a change in a firm's product and service offerings, with movement to selling through a digital channel, had a positive impact on firm sales. However, flexibility through a combination of change in product and service offerings with workforce location changes had negative impacts. Robustness analysis indicates that negative impacts worsen in countries with higher digitization and in manufacturing and retail firms as compared to service firms, indicating the inflexibility of physical goods–based business models. Results highlight dimensions through which technology-based flexibility can take place and the benefits of flexibility on firm performance.

This study provides managerial insights into technology-based operational flexibility mechanisms that can be employed for building performance resilience during unexpected disruptions. Research findings inform firms facing supply chain challenges and inflation pressures of business today.

This paper aims to provide a discussion on the interface and interactions between data, analytical techniques and impactful research in humanitarian health supply chains. New techniques for data capturing, processing and analytics, such as big data, blockchain technology and artificial intelligence, are increasingly put forward as potential “game changers” in the humanitarian field. Yet while they have potential to improve data analytics in the future, larger data sets and quantification per se are no “silver bullet” for complex and wicked problems in humanitarian health settings. Humanitarian health supply chains provide health care and medical aid to the most vulnerable in development and disaster relief settings alike. Unlike commercial supply chains, they often lack resources and long-term collaborations to enable learning from the past and to improve further.

Based on a combination of the authors’ research experience, interactions with practitioners throughout projects and academic literature, the authors consider the interface between data and analytical techniques and highlight some of the challenges inherent to humanitarian health settings. The authors apply a systems approach to represent the multiple factors and interactions between data, analytical techniques and collaboration in impactful research.

Based on this representation, the authors discuss relevant debates and suggest directions for future research to increase the impact of data analytics and collaborations in fostering sustainable solutions.

This study distinguishes itself and contributes by bringing the interface and interactions between data, analytical techniques and impactful research together in a systems approach, emphasizing the interconnectedness.

The purpose of this study is to investigate the impact of titanium oxide (TiO₂) filler on the abrasive wear properties of bamboo fiber reinforced epoxy composites (BFRCs) using a Taguchi approach. The study aims to enhance the abrasive wear resistance of these composites by introducing TiO₂ filler as a potential reinforcement, thus contributing to the development of sustainable and environmentally friendly materials.

This study focuses on the fabrication of epoxy/bamboo composites infused with TiO₂ particles within the Wt.% range of 0–8 Wt.% using hand layup techniques. The resulting composites were subjected to wear testing according to ASTM G99-05 standards. Statistical analysis of the wear results was carried out using the Taguchi design of experiments (DOE). Additionally, an analysis of variance (ANOVA) was used to determine the influential control factors impacting the specific wear rate (SWR) and coefficient of friction (COF).

The study illuminates how integrating TiO₂ filler enhances abrasive wear in epoxy/bamboo composites. Statistical analysis of SWR highlights abrasive grit size (grit) as the most influential factor, followed by normal load, Wt.% of TiO₂ and sliding distance. Analysis of the COF identifies normal load as the primary influential factor, followed by grit, Wt.% of TiO₂ and sliding distance. The Taguchi predictive model closely aligns with experimental results, validating its reliability. The morphological study revealed significant differences between the unfilled and TiO₂-filled composites. The inclusion of TiO₂ improved wear resistance, as evidenced by reduced surface damage and wear debris.

This research paper aims to integrate TiO₂ filler and bamboo fibers to create an innovative hybrid composite material. TiO₂ micro and nanoparticles show promise as filler materials, contributing to improved tribological properties of epoxy composites. The utilization of Taguchi’s DOE and ANOVA for statistical analysis provides valuable guidance for academic researchers and practitioners in optimizing control variables, especially in the context of natural fiber reinforced composites.

This paper aims to explore the impact of brand authenticity dimensions (i.e. aesthetic, symbolism, heritage, originality, quality commitment and virtue) on consumer engagement in the context of social media. This study answers to the need of scholars to understand consumer behaviour towards family and non-family firms’ brand authenticity constructs and for practitioners to find the correct levers to increase consumer engagement.

Top 10 European family firms with a retrievable Facebook (FB) page from the Global Family Business Index have been selected. Then, the study analysed family firms’ social media consumer engagement versus their non-family business direct competitors on a sample of 21.664 FB posts over a four-year period, leveraging multi-group analysis.

The results outline that three out of six brand authenticity dimensions posted on FB are statistically arousing more interactions respect to non-authenticity-related contents when posted by family firms. However, there are no statistically significant findings when brand authenticity content is posted by the non-family competitors.

This research is helpful for practitioners and entrepreneurs who might want to strengthen their social media brand strategies. With this regard, the study provides insights on which elements of brand authenticity are perceived by consumers as more engaging and which levers to use when communicating the familiness of the company.

To the best of authors’ knowledge, this is one of the earliest studies crosscutting the family business and brand authenticity literature streams to conduct an empirical analysis based on official FB data with a data set of over 20,000 observations. Moreover, this study assesses that not every dimension of the brand authenticity construct is relevant in the context of social media and that its effectiveness depends on the firms’ familiness.

This study aims to follow a rigorous approach to identify, critically analyze and synthesize 75 papers published from 2000 to 2022.

The study presents a systematic literature review on identity expressiveness (IE), clarifying and expanding what is currently known about the concept.

To synthesize current knowledge on IE, the study uses the overarching framework of antecedents-phenomenon-consequences, using this same framework to identify gaps and future research directions. The findings show individual and brand-related factors such as the need for uniqueness and anthropomorphism as antecedents of IE, and eWOM/WOM, impulse purchases and upgrading to more exclusive lines as consequences of IE.

The study contributes to theory by synthesizing and mapping current understanding of the state of knowledge on the concept of IE while highlighting gaps in the extant literature and paving future research directions for scholars in the field.

The study offers useful insights for practitioners, broadening marketers’ actionable options in identity-based marketing. Marketers can use insights from this study to inform marketing strategy and communication campaigns for different types of brands.

To the best of the authors’ knowledge, this study is the first of its kind and offers an integrative review of the current literature on IE, thus enhancing understanding of the concept, its antecedents and consequences. The study also contributes to knowledge by highlighting future research priorities for researchers in this field of enquiry.

Digitalization is revolutionizing the retail sector as today's consumers prefer a seamlessly integrated, fluid and irritation-free shopping experience enhanced with artificial intelligence (AI)-powered technologies. Literature highlights gaps in the understanding of the shopping experience in an omnichannel context, involving aesthetic, cognitive and affective experience dimensions. This research highlights the direct effects and the mechanism triggered in the presence of such device.

A sample of 259 consumers was interviewed at the point of sale. Data have been collected after a shopping experience in two concept stores belonging to the same fashion brand: (1) not equipped with AI-powered technology and (2) equipped with these tools. The measurement scales were validated through ANCOVA analysis and causal relationship analysis with structural equation modeling.

The results show that the presence of an in-store AI-powered technologies in a connected store generates a higher aesthetic reaction when visiting the store, a higher absorption when shopping through the flow and a higher intent to purchase. The authors further investigate the underlying mechanism triggered by the presence of this technology, which enables the authors to outline their consequences regarding purchase intention.

The study, conducted within an actual connected store in France, explores the impact of AI technology in connected retail environments on consumer responses. It is an early research in this field, shedding light on a rarely explored area. The authors’ research addresses a significant gap, providing insights into AI-driven retail experiences.

Omnichannel sales have provided new impetus for the development of catering merchants. The authors thus focus on how catering merchants should manage capacities at the ordering, production and delivery stages to meet customers’ needs in different channels under third-party platform delivery and merchant self-delivery. This is of great significance for the development of the omnichannel catering industry.

This paper formulates the capacity decisions of omnichannel catering merchants under the third-party platform delivery and merchant self-delivery mode. The authors mainly use queuing theory to analyze the queuing behavior of online and offline customers, and the impact of waiting time on customer shopping behavior. In addition, the authors also characterize the merchant’s capacity by the rate in queuing model.

The authors find that capacities at ordering stage and food production stage are composed of base capacities and safety capacities, but the delivery capacities only have the latter. And in the self-delivery mode, merchants can develop higher safety capacities by charging delivery fees. The authors prove that regardless of the delivery mode, omnichannel sales can bring higher profits to merchants by integrating demand.

The authors focus on analyzing the capacity management of omnichannel catering merchants at the ordering, production and delivery stages. And the authors also add the delivery process into the omnichannel for analysis, so as to solve the problem of capacity decision-making under different delivery modes. The management of delivery capacity and its impact on other stages’ capacities are not covered in other literature studies, which is one of the main innovations of this paper.