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Internet of things (IoT) and big data (BD) could change how the societies function. This paper explores the role of IoT and BD and their impact on customer relationship management (CRM) investments in modern customer service. The purpose of this paper is to develop an analytic hierarchy planning framework to establish criteria weights and to develop a general self-assessment model for determining the most important factors influencing the IoT and BD investment in CRM. The authors found that most studies have focused on conceptualizing the impact of IoT without BD and with limited empirical studies and analytical models. This paper sheds further light on the topic by presenting both IoT and BD aspects of future CRM.

The analytic hierarchy process (AHP) methodology is used to weight and prioritize the factors influencing the IoT and BD investment in modern CRM in the service industry. The AHP framework resulted in a ranking of 21 sustainability sub-factors based on evaluations by experienced information technology and customer service professionals.

The paper provides significant insight on the new frontier of CRM, focusing on the use of IoT and BD and the respective solutions to address them were identified. This study primarily contributes in providing the process of effectively managing and implementing IoT and BD in big businesses by identifying the connecting link between firms and customers.

The understanding of new frontier of CRM connective via IoT and BD can solve the dilemmas and challenges linked to the practice of implement IoT and BD in the information systems field. The study provides valuable information and critical analysis of IoT and BD with regard to the integration of CRM. Finally, this study further provides directions for future researchers.

IoT and BD are a growing phenomenon, which business decision-makers and information professionals need to consider seriously to properly ascertain the modern CRM dimensions in the digital economies. They also should embrace the proper CRM innovation, which is powered by IoT and BD, and discover how IoT and BD can bring the next level of maturity to CRM “CRM of everything.”

The purpose of this study is to make an attempt to identify the factors responsible for the adoption of an artificial intelligence (AI)-integrated customer relationship management (CRM) system in Indian organizations with a special focus on security and privacy issues.

This study was conducted for the identification of factors responsible for the adoption of the AI-integrated CRM system in Indian organizations focusing attention on security and privacy perspective. For this, the adoption theories and models have been studied. The literature available in this context has also been studied with a focus on security and privacy issues. After the initial study, few hypotheses have been formulated and a conceptual model has been developed. These hypotheses were validated with the help of statistical tools by conducting sample survey with 324 usable responses against 36 questionnaires.

The results of this study highlight that of the eight hypotheses conceptually formulated, one hypothesis was not supported as is evident from the application of statistical analysis. This is the influence of perceived ease of use on attitude of the stakeholders intending to use the AI-integrated CRM system in Indian organizations. The results also transpire that the model so provided has achieved 87% explanative power.

The model so provided has taken the help of the technological acceptance model. It has also used the issues circumscribing menace of security and privacy vulnerabilities. Consideration of the technological acceptance model and aspects of issues of security and privacy has enriched the model rendering its explanative power to 87%.

The model is simple. Practitioners can execute this model without having any complexity. The policymakers could also get inputs from the model, as it has focused specially on security and privacy issues that could help to enhance the trust of the potential users.

Not many studies are found covering the adoption of the AI-integrated CRM system by Indian organizations with a special focus on security and privacy aspects. In this light, this study is a novel attempt.

The purpose of this paper is to present a comparison between the traditional methods for the calculation of customer relationship performance and the modern metrics suggested by the current literature in business-to-business (B2B) markets using the Greek maritime shipping industry as an example.

The primary research was conducted in two phases: quantitative analysis of actual measurements and qualitative evaluation of the results. More specifically, in the first phase, the measures used were a collection of traditional and modern customer relationship management (CRM) metrics applied to actual historical data along with statistical data for actual customers of a company supplying services for maritime transportation of containers in the Greek international trade market. For the qualitative evaluation of these results, a semi-structured interview was carried out with seven “specialists/experts” in this business sector, who provided an assessment of the relative worth of each set of CRM measures.

The use of modern customer-centred metrics (Share and Size of Wallet, recency, frequency, monetary value) in the shipping sector of Greek industrial activity is the most profitable and efficient means of decision-making. The qualitative research showed that the customer-centred metrics were judged to be more effective and useful, as they provided a multi-dimensional and multi-layered picture of the current and future situation for the company and its customer base.

To ensure confidentiality of personal information, the research did not use, examine or evaluate the individualized data to preserve the anonymity of the survey sponsor and their specific customers.

This is the first study that examines the effectiveness of different types of CRM metrics in the B2B market, which has, until now, suffered a dearth of empirical studies in the field, especially in the context of national economies that face intense international trading problems and significant reductions in activity in their maritime shipping industry due to the economic recession.

The purpose of this paper is to develop a conceptual framework to check if an organization is ready to adopt an AI-integrated CRM system. The study also analyzes different situations which can provide a comprehensive check list in the form of indicators that could provide a signal indicating whether the organization is ready to adopt an AI-integrated CRM system by capturing actionable and appropriate data.

The paper is a general review, and appropriate literature has been used to support the conceptual framework.

The key findings of this study are the different indicators that make up the conceptual framework. This framework can help organizations to check at a glance whether they are ready to adopt AI-integrated CRM system in their organizations. Specifically, it has been identified that different approaches are needed to tackle various types of customer data so that those may be made fit and actionable for appropriate utilization of AI algorithms to facilitate business success of an organization.

The paper has elaborately discussed the different approaches to be undertaken to calibrate and reorient the various kinds of actionable data and the contemplated challenges one would face in doing so. This would help the practitioners that how the data so captured can be made fit for action and utilization toward application of AI technologies integrated with existing CRM system in an organization.

This study is claimed to be a unique study to provide a conceptual framework which could help arranging and rearranging of captured data by an organization for making the data fit and ready for use with the help of AI technologies. This successful integration of AI with CRM system can help organizations toward taking quick and automated decision-making without much intervention of human beings.

Martin’s Big Words: The Life of Dr Martin Luther King, Jr is a timeless book well-known among K-6 teachers, students, librarians and book-lovers throughout the USA. This multi-award winning picture book provides readers with insight into Dr Martin Luther King Jr’s life and the oppression and progress of African Americans before and during an era known as the modern US Civil Rights Movement (CRM). The biography outlines the period’s equity issues, and serves as a springboard for this upper elementary lesson. While Dr King played an iconic role, there were many other individuals involved in the CRM, most of whom students do not know. The purpose of this paper is to offer varying perspectives related to lesser known CRM leaders, protesters, advocates, perpetrators and bystanders.

Technology is incorporated through online research, videos and productions; thus, students actively engage in making connections to various individuals’ points of view, those both supportive and oppositional. Students conduct research while responding to higher-order, critical-thinking questions regarding groups and forces of the CRM. Then, they expand knowledge through jigsaw research activities by collecting information, responding to inquiry questions and presenting relevant evidence-based information about CRM contributors, perpetrators and bystanders.

This is a National Council for the Social Studies (NCSS) Notable Tradebook Lesson Plan.

This is a NCSS Notable Tradebook Lesson Plan.

In a modern business scenario, firms have implemented customer-centric approaches to enable customer relationship management (CRM) to trigger business excellence. Business strategies are modernizing business marketing operations that mainly focused on the retention of profitable customers. The purpose of this study is to empirically investigate the impact of marketing strategies (MS), information technology support (IT-S) and knowledge sharing (KS) in the effect of CRM in the pharmaceutical sector of Punjab, Pakistan.

Data were collected from the field force of national and international pharmaceuticals companies (N = 263) through a convenience sampling technique. Partial least squares structural equation modeling was used to examine data in SmartPLS 3.2.6.

The results indicated that IT-S and KS mediate the relationship between MS and CRM. More specifically, MS positively develops CRM through IT-S and KS.

This research contributes to the existing literature of pharmaceuticals by disclosing the field-force (medical representatives) specific role in developing CRM performance between pharmaceuticals firms and health-care physicians that are mainly based on knowledge advancement and influence these firms to adopt customer-centric business approaches to gain a competitive advantage to drive firm profitability.

One of customer relationship management (CRM) activities involves soliciting customer feedback on product and service quality and the resolution of customer complaints. Inevitably, companies must deal with large number of CRM messages from their customers either through e‐mails or from work logs. Going through those messages is an important but tedious task for managers or CRM specialists in order to make strategic plans on where to place the resources to achieve better CRM results. In this paper, we present a methodology for making sense out of CRM messages based on text clustering and summary techniques. The unique features of CRM messages are the short message length and frequent availability of correlated CRM ratings. We propose several novel techniques including organizational concept space, Web mining of similarity relationships between concepts, and correlated analysis of text and ratings. We have tested the basic concepts and techniques of CRM Sense Maker in a business setting where customer surveys are used to set strategic directions in customer services.

The purpose of this paper is to propose a model to understand the role of customer relationship management efforts in building, sustaining and enhancing customer loyalty (CL).

This paper reviews extant literature in customer relationship management (CRM), customer experience management (CEM) and CL, with a particular emphasis on exploring the relationships between these proposed domains.

The CRM efforts, customer acquisition, retention and experience, are suggested to have positive influence on attitudinal and behavioural loyalty. A model for testing the associations of customer relationship efforts to various forms of CL, including the satisfaction, trust and commitment as mediators in CRM-CL link are proposed.

This paper represents a first attempt to build and propose a conceptual framework of CRM–CL. This is an indicative research than a conclusive one. Therefore, research implications are to perform the empirical testing of model in different business environments.

This application of proposed model in a business environment will be helpful for the marketing practitioners to well understand the customers’ changing expectations as well as to prioritize the marketing functions. The emphasis and right calculation about the acquisition, retention and experience decisions would be helpful to marketers to know the expected profitability of customers.

This is the first paper to provide a comprehensive integrated model of CRM and CL to understand the effects of CRM efforts on various forms of CL.

Processes in customer relationship management (CRM) are classified as knowledge‐intensive processes. This paper seeks to provide a framework for knowledge management (KM) support of CRM processes and to show how this framework was applied in three action research cases.

In a long‐term cooperation with several leading companies the authors developed a framework for customer knowledge management (CKM) and applied this framework in several action research cases. Additionally, further case studies have been conducted which support the framework. A selection of three action research cases is presented.

Six core processes of CRM and four building blocks of KM to support these processes we identified. Each of these cases demonstrates the application of the framework and the implementation of the appropriate subset of CKM.

The cases support the CKM model. All cases presented here come from the financial services industry, thus the framework still needs to be applied in other industry segments as well.

The cases evaluate the applicability, utility and efficacy of the CKM framework and show how it can help to make managerial decisions concerning the KM support of CRM processes.

The paper provides a framework classifying the processes in CRM and the KM building blocks to support these processes. To researchers it provides an evaluation of the presented framework and shows potential fields for further research. It also gives practical advice to managers who plan CRM initiatives.

The purpose of this paper is to examine the use of technology in customer relationship management (CRM) support capabilities by using an environmental contingency perspective. By examining the moderating effects of micro- and macro-environmental characteristics in which CRM support capabilities are used, the authors seek to extend the literature on CRM technology effectiveness in both customer commitment and overall firm performance. The authors also seek to advance managerial knowledge about CRM support capability technology utilization strategies in various market offering and dynamic market settings.

The authors utilized a questionnaire to collect data from a sample of 276 small business CRM managers across a wide range of industries. Measures were adapted from the existing literature, and these were largely multiple-item measures of latent variables. The hypotheses were tested using a combination of Ridge regression and a bootstrapping test of mediation. In addition, residual centering was used to reduce multi-collinearity in the interaction analysis.

The contingency/fit analysis performed in this research highlights the complex nature of the use of technology in CRM support capabilities. The benefits of a man vs a machine CRM support capability depend on the support function (whether marketing, sales, service, data access or data analysis), as well as upon the characteristics of the operating environment. Machine-based marketing support is positively related with customer commitment in turbulent markets, and machine-based service support is preferred in technologically turbulent markets. Sales support, on the other hand, is positively related to customer commitment in technologically turbulent markets when performed by man rather than machine.

CRM support capabilities differ across firms and markets, thus a “one size fits all” approach is not appropriate. This research shows under what conditions a machine-based approach to CRM can be effective for small businesses.

This research is the first to consider market offering and turbulence variables as moderators of the relationship between technology use in CRM support capabilities and customer commitment. Taking this contingency approach, the authors find that resource-based competitive advantage is obtainable based on the fit of the resources (e.g. CRM capabilities) to the environmental characteristics of the firm. Through this perspective that is unique to CRM research, the authors are able to provide both general and specific recommendations to managers and researchers.