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Today the mobile apps are helping customers in every means of their life by exploring information related to electronic items and even for food items also. Therefore, the main aim of this study is to examine the influencing role of psychological and technological attributes on customer conversion to use food ordering apps.

Convenience sampling method was used to collect responses from the customer's age between 18 and 35 years to get more representation of society. 374 customer's data has been used for structural equation model analysis with the help of SmartPLS 3.0 and SPSS-20 software.

Findings showed that customer conversions are positively influenced by perceived ease of use, perceived usefulness, perceived incentives, perceived information, customer relationship management and order management system. In contrast, the perceived price and visual design show insignificant influence.

Research outcome provides some valuable insights to provide direction to all online food aggregators to design their apps according to customers need. Thus, the authentic customer reviews and the facility of providing feedbacks are very fruitful for attracting new user while using and placing orders through theses apps.

Study suggested that observing satisfaction and dissatisfaction levels of the customer helps in enhancing the facilities of food ordering apps, so that the customer would enjoy the whole order process seamlessly, which automatically leads to customer conversions.

Major contribution of this study is the empirical analysis of psychological and technological attributes on customer's conversion towards food ordering app.

The first research objective is to understand the role of digital [artificial intelligence (AI)] technologies on user engagement and conversion that has resulted in high online activities and increased online sales in current times in India. In addition, combined with changes such as social distancing and lockdown due to the COVID-19 pandemic, digital disruption has largely impacted the old ways of communication both at the individual and organizational levels, ultimately resulting in prominent social change. While interacting in the virtual world, this change is more noticeable. Therefore, the second research objective is to examine if a satisfying experience during online shopping leads to repurchase intention.

Using primary data collected from consumers in a developing economy (India), we tested the theoretical model to further extend the theoretical debate in consumer research.

This study empirically tests and further establishes that deploying AI technologies have a positive relationship with user engagement and conversion. Further, conversion leads to satisfying user experience. Finally, the relationship between satisfying user experience and repurchase intention is also found to be significant.

The uniqueness of this study is that it tests few key relationships related to user engagement during this uncertain period (COVID-19 pandemic) and examines the underlying mechanism which leads to increase in online sales.

The author prefaced this talk given at the CIES Executive Congress in Monte Carlo in June with the words that his subject — improving productivity through more rational co‐operation between supplier and retailer — was an issue of great importance. His aim, however, was not to startle anyone with new insights into product coding, cage pallets or shrink wrapping. He intended to get his audience to think along particular lines, so that any opportunities which exist for retailers and suppliers to work together more productively would receive more top management attention, resulting in happier customers and more profitable enterprises.

The purpose of this paper is to evaluate the relationship between strategy and customer lifetime value (CLV). A new model was proposed for defining customers’ values based on the RFM model and segmenting bank customers using the K-means algorithm. In addition, the authors combined a new category with the delta model in order to analyze the behavior of each cluster.

This case study was based on an applied method following its objectives and a descriptive-analytic method in terms of data collection. In this research, the AHP, data mining and K-means clustering methods, as well as the discriminant analysis were applied for computing the weights of the indices, examining the relationship between the identified variables, clustering the records and ensuring the clustering accuracy based on the RFM model, respectively.

The paper confirmed the relationship between the strategies and CLV. For a cluster whose strategy was the best product, customers had a minimal CLV. For a cluster whose strategy was based on total customer solutions, customers had a median CLV. For a cluster whose strategy was a lock-in system, customers had a maximal CLV. The results suggested that the delta model with these three strategies could act as the CLV developers in two stages: conversion of transient customers to attached customers and conversion of attached customers to locked-in customers.

One of the limitations of this study was the lack of access to all the bank accounts and assessment of only the strategy type, while highlighting the exact association between every component of the strategies (e.g. structure, environment, etc.) and CLV as a dependent variable deemed to be of a great necessity. Hence, it is recommended that several studies on the relationships presented in this paper be performed to provide further insights into and guidelines on this issue in the future.

This study emphasized the relevance of strategy and CLV. Managers should differently treat customers in distinct CLV and loyalty levels. In other words, managers must segment their customers based on CLV and apply appropriate strategies for each segment.

This research tried to fulfill an identified need to study how strategy can be effect CLV through the application of the delta model with three strategic options.

The motivation for this paper arises from the evolution of the e‐commerce which has provided new means for retailers to serve customers. Pure e‐tailers and clicks‐and‐mortars are two business models of this new paradigm. It aims to study the particularities of pure e‐tailer (Amazon.com) and clicks‐and‐mortars (Walmart) with special focus on their dot com supply chains.

Strengths, weaknesses, oppositions, threats (SWOT), the Five Forces Model and Financial Performance Metrics analyses were used to draw comparisons and contrasts between Walmart.com and Amazon.com supply chains.

The paper finds that both companies serve their customers effectively through their efficient supply chains; however, due to the infancy of e‐commerce, both business models still face important challenges.

Amazon.com and Walmart.com have different supply chain models, as well as, strengths and weaknesses. They both face the same opportunities and threats as the e‐commerce industry grows rapidly. Analysis shows how lessons from one business entity can be applied to the other in order to bring even more efficiencies to both e‐tailers’ and clicks and mortars’ supply chains.

Based on the perspective of knowledge management capability, this paper aims to reveal the internal mechanism of the digital empowerment of mobile social platforms to improve the operational performance of Chinese traditional retail enterprises. Such improvements have crucial theoretical value and practical implications for Chinese traditional retail enterprises to achieve transformation and sustainable development.

This study applied the typical analysis method, selected China’s leading mobile social platform, WeChat, as a typical case, and observed and analyzed the public data of the traditional retail industry and social platforms and interviews with relevant enterprises. On this basis, this study used the inductive and deductive methods of qualitative research to conduct an in-depth analysis of the mechanism by which WeChat’s digital empowerment improves the operational performance of Chinese traditional retail enterprises. It also discussed the critical role and path knowledge management capabilities play in this mechanism.

This research demonstrated that mobile social platforms empower Chinese traditional retail enterprises to build diversified digital channels, enhance the knowledge acquisition capability of enterprises and thus improve their performance; empower Chinese traditional retail enterprises to build digital community networks, enhance the knowledge diffusion capability of enterprises and thus improve their performance; and empower Chinese traditional retail enterprises to integrate online and offline businesses, enhance the knowledge integration capability of enterprises and thus improve their performance.

This study clarifies the internal mechanism of how the digital empowerment of mobile social platforms can improve the performance of Chinese traditional retail enterprises. This mechanism implies that knowledge management capabilities (knowledge acquisition, diffusion and integration capability) are the underlying logic for Chinese traditional retail enterprises to achieve higher performance levels. This has important practical implications for managers of Chinese traditional retail enterprises to leverage the digital infrastructure of mobile social platforms to achieve the sustainable development of enterprises.

This study provides an in-depth analysis of how the traditional retail industry uses digital social platforms to improve operational performance from the perspective of knowledge management capabilities, which can further promote the theoretical research and practical development of digitalization and knowledge management. At the same time, this study explored the research on the operational performance of Chinese traditional retail enterprises from the perspective of knowledge management capabilities and expanded the research on knowledge management in related fields. The authors have initially sorted out the impact of knowledge management capabilities on the operational performance of Chinese traditional retail enterprises in the digital era. This will help better understand the role and function of knowledge management in strategic transformation and expand the application of knowledge management theory.

A customer's journey of searching for a product or service, evaluating it, purchasing it, using it, recommending it, rebuying it or rejecting it is unique in itself. Organisations always have dreamt of getting inside the customers' minds and trying to understand what's happening inside at each of these steps. This chapter explains the customer journey concept and the analysis of the various components of the customer journey. We highlight that the firms need to understand the customer journeys and the multiple touchpoints they interact with to create a worthwhile customer experience. The chapter lists out the various touchpoints, including social/external touchpoints, customer-owned touchpoints, partner-owned touchpoints and brand-owned touchpoints. We discuss three frameworks that can be used by a firm to understand design a customer journey. These frameworks include AIDA (awareness, interest, desire and action), MAI (measure, analyse and improve) and journey maps. The chapter recommends the various steps which a firm can use to create a journey map. In the end, we create a linkage between the customer journey and business transformation. The chapter builds a case for the application of customer journey management by pointing out that it is a complex phenomenon, and the firms should use a structured approach to design and manage the customer journey.

The versatility of customer relationship management (CRM) systems has kept these technologies popular over the years. These solutions have been integrated into organizations of all sizes, from large corporations to small- and medium-sized enterprises. Similarly, CRM systems have also found applications in all types of industries and business sectors. All this has been the driving force behind the proliferation of CRM solutions around the world. In this chapter, the author not only reflects on the impact and democratization of CRM systems on business management and marketing strategies but also explores how these technologies can determine the company's income. In particular, the author presents an experiment that analyzes the extent to which the volume of annual investment in CRM solutions can be used to predict annual net income in a sample of companies. Using time series analysis and applying the autoregressive integrated moving average modeling technique, the researcher examines a sample of 10 companies from different industries, and countries, over a 20-year period. The results show the efficiency of the predictive models developed in nine of the 10 companies analyzed. The findings of this study allow us to conclude that there seems to be an association between the investments made in CRM solutions and the income of the companies that invest in these technologies.

With a gross revenue fast nearing £700 million, 115,000 employees and over 13 million customers, the gas industry is a vast enterprise, and discovery of natural gas in the North Sea has transformed it.

The advent of the new retail era witnessed the consumers’ demand shift from on the traditional product quality to on the full supply chain service quality, and product service and service manufacturing is gradually taking shape. The purpose of this paper is to propose whether there is a “quality bridge” in the dynamic evolution process of retail service supply chain (RSSC) and discuss the system role, steady-state characteristics and dynamic evolution mechanism of service quality in this dynamic evolution process.

This paper proposes the dissipation system structure of the RSSC under the steady-state quality constraint, constructs a Markov chain model (MCM) for the evolution of the service quality of RSSC, and tests the objective existence of the steady-state distribution of the service quality by taking Chinese HJ retail enterprises as samples.

The research value of this study is summarized as follows. The research finds that the evolution of service quality of RSSC is a dynamic and non-linear growth process, which has significant characteristics of complex adaptability and steady-state convergence. The study finds that the quality evolution process of the RSSC is a steady-state convergence process, and there is a steady-state distribution of quality in its co-evolution, in which different process input levels have a significant positive impact on the stable level of quality state. The study finds that the steady state of quality plays a crucial role in the collaborative evolution of the RSSC, that is, when the service quality reaches a certain steady state distribution, the operating efficiency and profit level of the whole chain will show an “explosive” growth trend.

Quality bridge, an original concept in this paper, represents the role of quality steady-state in the operation of RSSC. Based on Markov chain and system simulation tools, this paper verifies the existence of steady-state service quality and its positive effect on the co-evolution and sustainable development of RSSC. When the service quality reaches a certain steady distribution, the operating efficiency and income level of the whole chain will show n trend of explosive growth.