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The technology evolution compels retail networks to introduce unique business models to retain customers and to gain a competitive advantage. Customer reviews available through social media need to be taken into account by retail networks to design a model with unique service operations and marketing approaches that will improve loyalty by adding value to customers. Furthermore, the relationship between customer satisfaction and customer spending behaviour is very weak and needs further investigation. Hence the purpose of this paper is to understand how retail network leverage the potential of social media reviews along with unique service operations to satisfy customers. The study analyses the nexus of: a brand, promotional offers, service operations; and their interaction through social media reviews on customer satisfaction levels.

The authors develop a conceptual model for the social media era. The authors combine the idea of loyalty- and value-based models of Chatterjee (2013). The authors employed a survey questionnaire method to elicit opinions of retail customer satisfaction based on social media reviews, service operations and marketing efforts. The authors derive measures of the model from existing literature and expert opinion.

Social media reviews dramatically impact upon customer satisfaction. Similarly the empirical analysis identifies the significant and positive role played by service operations in customer satisfaction levels. Interestingly the authors did not find unequivocal support for brand satisfaction impacting on customer satisfaction. However, when promotions interact well with service operations, the level of customer satisfaction is significantly affected. Similarly the authors did not observe a positive outcome when there is an interaction between promotion and social media reviews. After reading the reviews, some potential buyers make a visit to store before making final decisions and surprisingly, promotional effects do not change their mind set.

Research findings confirm the importance of social media reviews, marketing and interaction between promotion and service operations enabling retail networks to build loyalty and value-based models. Based on customer behaviour, the study suggests a need to consider operational efficiencies when promoting sales; through careful planning, customer satisfaction and profitability levels can be increased. This sends a strong message to the retail network to defend their position within a very competitive business market.

The empirical evidence based on customer experience would be helpful for companies in integrating their operations and marketing efforts enabling them to convert different segment of customers such as “free riders (higher satisfaction and low profitability)” and “vulnerable customers (low satisfaction and higher profitability)” into “star customers (higher satisfaction and high profitability)”. Through a considered approach: combining social media reviews, marketing and operations, businesses will be better-placed to survive in the ultra-competitive social media-influenced era.

The COVID-19 pandemic has impacted all manufacturing sectors from basic products to luxury goods including the automobile industry. This has necessitated a new line of research on competency building, transparency, and sustainability in automotive supply chains. In this study, the authors examine the competencies required to improve the automotive supply chain routine operations to address the parts supply crisis from multitier suppliers in the post-COVID-19 environment. The authors also propose a list of competencies required in the automotive supply chains to deploy the transparency for sustainability (TfS) framework on a long-term basis.

The authors have adapted a cross-case study process using intervention-based research and a design science approach for use in this study and used multiple sources for data collection such as published literature, operational experience, and critical opinions of original equipment manufacturer representatives. The research design includes interviews with global OEMs practitioners as one of the relevant sources of information.

The impact of the COVID-19 pandemic outbreak on automotive manufacturing operations and global supply chains is unprecedented. The TfS framework cycle has been validated using the real-world semiconductor supply crisis which deals with multitier sustainable supply chain management (MTSSCM), and the authors found that there are competency gaps when compared with existing literature. The list of key competencies identified along with the formulation of design propositions to facilitate both the supply crisis and collaboration among automotive firms to enhance their business performance were also presented.

The COVID-19 pandemic is impacting the automobile sector significantly. This situation has created many opportunities and obstacles, but this paper only considers the automotive semi-conductor shortage situation, which may be resolved in the near future when there are more installed capacities. Therefore, it is unclear whether the proposed responses will result in long-term solutions. Further adjustments may be needed to revisit the TfS framework. The research paper only addresses the automotive side of the current supply crisis, but more sustainability issues may arise in the future, which need to be dealt with separately.

Research findings may prove particularly interesting to global automotive vehicle manufacturers, suppliers and policy makers who are seeking to understand multitier supply networks to resolve the current challenges associated with the post-COVID-19 pandemic situation.

In addition to contributing to developing competency requirements, this study enhances the evolving research stream of MTSSCM by linking it to wider research applications of intervention-based research coupled with design science.

This research is elucidating quality control theories to reduce variation in chocolate manufacturing process in the UK food company that will help maintain the processes stable and predictable. The purpose of this paper is to reduce defects of the output; to identify the root causes of variation; to establish and implement solutions to this variation problem; and to establish a control system to monitor and report any variation in the process.

The authors use experimental case study of a chocolate company to achieve the objective. In this paper, the authors predominantly use established theory define–measure–analyse–improve–control, customised to the case of the chocolate factory to reduce variations in production processes.

The results confirm that customised-traditional theoretical quality models will support manufacturing companies to maintain customer satisfaction while enhancing quality and reliability.

Implementation of customised approach reduced the rate of defect from 8 to 3.7 per cent. The implications of reduced variation are improved product quality; reprocessing elimination; and a more stable process that support sustainability and reliability in producing chocolates to meet customer needs.

The authors used an experimental-based case study approach to test with one company. Testing in multiple case companies may help to generalise results.

The research study experimentally tested quality approach with a real case company and hence the findings of this study can be applied to other cases working in similar settings.

At its peak, the COVID-19 pandemic has created disruption to food supply chains in the UK and for the entire world. Although societal changes created some resilience within the supply chains, high volatility in demand creates supply, logistics and distribution issues. This is reflected in the economic instability of businesses and small and medium enterprises (SMEs). In this paper, the authors explore factors behind this initial disruption in the supply chains and offer suggestions to businesses based on the established practices and theories.

The authors use mixed methods research. First, the authors conducted an exploratory study by collecting data from published online sources. Then, the authors analysed possible scenarios from the available information using regression. The authors then conducted two interviews with UK retail sector representatives. These scenarios have been compared and contrasted to provide decision-making points to businesses and supply chain players to tackle current and any future potential disruptions.

The findings from the current exploratory study inform the volatility of supply chains. The authors suggested some possible responses from businesses, during and after the pandemic.

The regression model provides a decision-making approach to help supply chain businesses during the pandemic outbreak. Once a complete data set of COVID-19 is available, the authors can create a resilience model that can help businesses and supply chains.

The purpose of this paper is to determine the nature of the relationship between service quality and desired customer behaviours in the leasing market using an appropriate service quality measurement model. The authors take a step further by recognising the possible differences in influence of service quality in private and corporate customers, and those business dealings with low, medium and high lease values.

The authors use deduction method to test the SERVQUAL in the German leasing market and the relationship between customer satisfaction and desired behavioural outcomes. The developed questionnaire is based on the 22-item scale of the SERVQUAL approach. Samples are selected based on convenience sampling.

The authors found differences in the levels of influence by SERVQUAL dimensions on corporate and private customers as well as among those customers with different leasing contract values. From the regression analyses, it is clear that “assurance” from the leasing company is the most common SERVQUAL dimension that has significant impact on overall service quality perceptions and obtaining customers satisfaction and loyalty (behavioural outcomes).

The authors recognised that all financial services are not created equally to meet customer demands. Hence, the customer expectations of service quality from these services will be different. The authors contributed to the marketing literature by studying customer perceptions of service quality by specifying financing aspects of financial services, i.e. leasing. The authors further contributed to the literature of SERVQUAL model in financial services by dividing customers into two different types of customers and those with diverse leasing contract values. The authors found that priorities given on service quality dimensions by them are different. These concepts were never considered in the literature. This also implies that future studies on financial services marketing need to recognise such differences in the research.

The purpose of this paper is to examine the role of digital supply chain (DSC) technologies in automotive supply chain resilience (SCR) practices to improve the supply chain performance (SC-Perf.) objectives of companies operating in the automotive industry. This study also compares the results of the associated SC-Perf objectives before and after the COVID-19 pandemic outbreak lockdown situation.

The authors undertook in-depth empirical research using a questionnaire survey to explore the performance of automotive supply chains. The sample for this study consisted of practitioners from supply chain entities such as automotive original equipment manufacturers, Tier-1 component manufacturers and lead logistics providers in Asia-Pacific (AP) emerging markets. Research questions, framework and hypotheses were developed using the literature review.

The research outcome from analysis of the data the authors collected from an emerging market context, specifically the automotive sector, emphasizes the role of DSC technologies and encourages the firm’s SCR practices which, in turn, supports the SC-Perf objectives. The DSC technologies competency moderates the SCR and SC-Perf objectives relation, and the moderation effect is higher for post-COVID-19 pandemic outbreak lockdown situation than at prior state.

The scope of the study is restricted to the automotive firms in the AP region. The data were collected from a representative sample of the population through a questionnaire survey. The small size of the sample incurs a certain level of subjectivity.

This research provides practical insights for practitioners and academicians on DSC technologies’ influence in SCR practices to improve the firm’s SC-Perf. This research shares the literature insights on use of DSC technologies across the sector to allow the automotive firm to reassess the existing operational practices.

The paper adds insights on introducing or implementing DSC technologies across AP automotive firms to increase the operations’ performance by improving SCR practices and sustainability.

The purpose of this paper is to empirically identify key factors of UK food supply chains (SCs) that significantly contribute to CO₂ emissions (CO2e) taking into account the life cycle assessment (LCA). The UK food supply chain includes imports from other countries.

This research develops a conceptual framework from extant literature. Secondary data obtained from ONS and FAOSTAT covering from 1990 to 2014 are analysed using Multilinear Regression (MLR) and Stochastic Frontier Analysis (SFA) to identify the factors relating to CO₂ emissions significance, and the efficient contributions that are being made to their reduction in the UK food supply chains.

The study results suggest that Transportation and Sales/Distribution are the two key factors of CO₂ emissions in UK food supply chains. This is confirmed by two multivariate methods, MLR and SFA. MLR results show that transportation increases UK CO₂ emissions by 10 tonnes of CO₂ emissions from one tonne of fruits and vegetables imports from overseas to the UK Sales and Distribution reduces the UK CO₂ emissions by 1.3 tonnes of CO₂ emissions due to improved, technological operation activities in the UK. In addition, the SFA results confirm that the key factors are sufficient to predict an increase or decrease in CO₂ emissions in the UK food supply chains.

This study has focused on the LCA of the UK food supply chain from limited data. Future studies should consider Sustainability Impact Assessment of the UK food supply chain, identifying the social, economic, regulatory and environmental impacts of the food supply chain using a re-defined LCA (all-inclusive assessment) tool.

This research suggests that food supply chain professionals should improve efficiency, e.g. the use of solar energy and biogas, and also integrate low-carbon policies and practices in food supply chain operations. Furthermore, governments should encourage policies such as mobility management programmes, urban redevelopment and privatisation to enhance better transportation systems and infrastructure to continuously reduce CO₂e from the food trade.

Although logistics play a major role in CO₂ emissions, all logistics CO₂ emissions for other countries are not included in the ONS data. This research reveals some important insights into the UK food supply chains. Logistics and other food supply chain processes of importing countries significantly contribute to CO₂ emissions which are yet to be considered in the UK food SCs.

The COVID-19 situation affected the whole landscape of retailing in India and around the world. However, some businesses have used the pandemic-related difficulties into opportunities. E-tailing is one of the ways that helped people in India to continue shopping their essential products and choosing their luxury products without making any physical visits during the lockdown. This research understands the current situation through an observation study and suggests the e-tailing model suitable during the COVID-19 and beyond.

We used secondary data to make the observational study. We also conducted two case studies and interviews with grocery shops and an automotive company.

This research suggests a simple collaborative e-tailing model combining all supply chain players to reduce people’s movement, timely delivery and enhanced service to meet customers demand during the lockdown period.

This paper has considered two real cases for discussion and also obtained information from public domain. The proposed model has been discussed with the case companies, and it hoped to support business planning for online services.

In this paper, the authors aim to examine the impact of resource capabilities on customer loyalty of UK hotels. Understanding this impact will help organisations to improve customer satisfaction in order to obtain improved customer loyalty.

The authors use a relatively innovative data source, namely online ratings. They measure resource capabilities of a firm using customer ratings in terms of various operational criteria. Similarly, customer loyalty is measured using guests ' ratings on their intention to use the same service (stay again in the same hotel) and their intention to recommend the service to friends. The authors employ structural equation modelling to test research hypotheses.

The authors ' results indicate that there is a significant positive influence of resource capabilities on customer loyalty. They further find that the significant influence of resource capabilities on customer loyalty does not differ across hotels with various star ratings.

The authors looked at the online guest ratings available on a particular website, but it is only one of the many websites offering online hotel reservations, and not all customers that made hotel reservations using this e-booking facility would be inclined to leave feedback after their stay in the hotel. This limitation can be partially overcome by pooling similar data from a number of online hotel booking sites.

The most important managerial implication is that good resource capabilities of firms translate well into customer loyalty. Thus, managers should ensure good performance in terms of various hotel attributes – cleanliness, quality of room, facilities, and customer service – and also ensure that customers perceive good value for their money while staying in the hotel.

The authors applied structural modelling framework to verify the resource capability – performance link in the context of hotels. They used a relatively novel data source – online guest ratings of hotels – to understand the relationships between resource capabilities and customer loyalty.

In general, demand for functional products is dependent on a range of promotions offered in various retail outlets. To improve promotional sales many retailers collaborate with manufacturers for planning, forecasting and replenishment. The purpose of this paper is to hypothesize that collaborative forecasting will improve the forecast accuracy if all the partners can relate their demand forecast with underlying demand factors.

In this paper, the author uses a case study approach to study various demand factors of soft drink products of the UK based company which offers frequent promotions in retail outlets. The paper represents the case study findings in a conceptual framework called Reference Demand Model (RDM). Further, the case study findings are validated empirically by means of multiple linear regression analysis using actual sales data of the case company.

Surprisingly, some of the demand factors specified as very important by the case company are not found to be highly significant for actual sales. The paper uses the identified demand factors to suggest levels of collaboration.

Understanding the importance of product specific demand factors through regression models and incorporating the same in managerial decision making will aid managers to identify the necessary information to make accurate demand forecasts.

This approach unveils the presence of three levels of collaboration namely preparatory, progressive and futuristic levels among supply chain partners based on the information exchange. The proposed method will aid decision making on information sharing and collaborative planning among manufacturer and retailers for future promotional sales.