Intelligent Business Processes in CRM - Exemplified by Complaint Management

Customer relationship management (CRM) is becoming a critical source of competitive advantage for businesses today. However, many CRM business processes are deficient and inflexible. For example, many customers are dissatisfied with complaint management. Still, companies seldom systematically adapt the complaint management process. In theory, operational and analytical CRM form a closed loop: analytical CRM uses business intelligence (BI) tools to analyze operational data and the knowledge gained is used for continual optimization of operations. One special approach in establishing this loop is to continually support decision points in operational processes with knowledge from BI. In this way, the use of BI becomes an integral part of business processes, which are then referred to as intelligent business processes. However, in CRM not much is known about this approach. Based on an extensive review of the literature, the study explores the state of theory and practice in the field of intelligent business processes in CRM, with special attention to complaint management because of its considerable importance and application potential. In particular, the conceptual framework of intelligent business processes in CRM is depicted and two implementation options are identified: embedded intelligence and business rules. Focusing on complaint management, evidence on intelligent business processes is systematically documented, weak points are identified, and a research agenda for the shift to more intelligent processes is presented

Setting B2B digital marketing in artificial intelligence-based CRMs: A review and directions for future research

[EN] The new business challenges in the B2B sector are determined by connected ecosystems, where data-driven decision making is crucial for successful strategies. At the same time, the use of digital marketing as a communication and sales channel has led to the need and use of Customer Relationship Management (CRM) systems to correctly manage company information. The understanding of B2B traditional Marketing strategies that use CRMs that work with Artificial Intelligence (AI) has been studied, however, research focused on the understanding and application of these technologies in B2B digital marketing is scarce. To cover this gap in the literature, this study develops a literature review on the main academic contributions in this area. To visualize the outcomes of the literature review, the results are then analyzed using a statistical approach known as Multiple Correspondence Analysis (MCA) under the homogeneity analysis of variance by means of alternating least squares (HOMALS) framework programmed in the R language. The research results classify the types of CRMs and their typologies and explore the main techniques and uses of AI-based CRMs in B2B digital marketing. In addition, a discussion, directions and propositions for future research are presented.In gratitude to the Ministry of Science, Innovation and Universities and the European Regional Development Fund: RTI2018-096295-BC22.Saura, JR.; Ribeiro-Soriano, D.; Palacios Marqués, D. (2021). Setting B2B digital marketing in artificial intelligence-based CRMs: A review and directions for future research. Industrial Marketing Management. 98:161-178. https://doi.org/10.1016/j.indmarman.2021.08.006S1611789

Supporting Online Customer Feedback Management with Automatic Review Response Generation

The growing amount of online reviews plays a significant role in a business' image and performance. Businesses in the hospitality industry often lack necessary resources to organize and manage online customer feedback and are therefore likely to search for alternative ways to handle this. AI-based technologies may offer valuable solutions. However, there is currently little research on if and how AI solutions may support the process of responding to online customer feedback in the hospitality industry. This paper presents and evaluates a concept for assisting customer feedback management with automatically generated responses to online reviews. Our solution contributes to ongoing investigations into text generation applications for supporting human authors and also proposes new approaches and potential business models for managing online customer feedback

Critical success factors of medical technology supply chains

This paper investigates Critical Success Factors that affect the performance of organisations involved in Medical Technology supply chains (MTSCs) in Germany. The Medical Technology sector in Germany is considered an innovative, fast-growing and promising industry, being third behind the USA and China as the biggest market in the world, worth 29.9 billion euros in 2017. MTSCs in this country are under pressure from health service funding and cheaper imports, primarily from China. Consequently, supply chain success is of high importance and OEM operational improvements are critical. This exploratory study involved a multiple case study approach where 15 OEMs within German MTSCs were investigated. Following within-case and cross-case analysis, empirical results led to the development of testable propositions, which constitute a foundation for further research investigation. The findings show that there are six, prioritised Critical Success Factors for MTSCs that include sales and operations planning, product development process, and quality and compliance. These findings challenge existing assumptions about Critical Success Factors within MTSCs, providing practitioners with strategies showing that re-prioritised CSFs should improve operational performance of OEMs

Complaint management expectations: an online laddering analysis of small versus large firms

This study explores complaint management expectations in business relationships, particularly the qualities and behaviours that affect buying companies as part of the complaint handling encounter with a supplier. An exploratory empirical study uses a hard laddering approach which also allows us to compare the expectations of large and small companies to understand size-effects. The research indicates that complaining companies perceive disruptions of their supplier relationships in the context of the business network within which they are embedded, especially vis-à-vis the benefits associated with long-term supplier ties. However, these network concerns are more pronounced for large companies. Issues of effective complaint management in business-to-business settings therefore need to be addressed not just as isolated managerial activities with limited benefits for the parties involved, but should be seen as being part of a wider activity set of strategic networking activities with an impact on whole business systems. Thus, the findings enrich the existing limited stock of knowledge on the context of complaint management in business relationships and networks

The Digitisation of Sanitation: Transformation to Smart, Scalable and Aspirational Sanitation for All

In 2016 the Toilet Board Coalition ran a Feasibility Study to explore the potential role of mobile and digital applications to drive efficiencies and consumer demand in sanitation business models operating in low-income markets. The following questions were at the centre of our inquiry:- How are sanitation businesses operating in low-income markets using mobile and digital applications in their businesses today?- How are sanitation businesses and entrepreneurs thinking about next generation opportunities for mobile and digital applications for their businesses in the future?- What is needed to build the ecosystem for the digitisation of sanitation for the low income markets?Is there commercial interest and demand from large industrial operations to become buyers and investors into the system? This paper presents the findings of our study in the form of a thought piece on the topic of the digitisation of sanitation for all. Our intent is to present a number of business opportunity spaces, where we believe that value has been left on the table and customer needs unmet, to be explored further in the decade ahead.

Revenge or Reconciliation? A Rejection-Based Model of Firm-Induced Relationship Termination

This study is the first to examine the effects of firm-induced relationship termination on customer rejection perceptions and firm-related outcome behaviors. A research model is developed that focuses on several key issues with respect to the post-termination process. First, the study explores how direct versus indirect termination styles influence a consumer’s feelings of relational evaluation. The author hypothesizes that indirect termination strategies lead to lower levels of rejection upon the dissolution of the relationship. Second, the author examines how the level of perceived rejection experienced by customers affects their subsequent emotions. Specifically, as a result of this rejection, customers may experience betrayal or yearning for the lost relationship. Third, the moderating effect of emotional attachment on the emotions that are present following rejection is examined, with results showing that an increased sense of attachment leads to greater feelings of betrayal as well as yearning. Finally, as a result of these emotions, the study sheds light on how customers behave upon being rejected; namely, whether they choose to seek revenge or attempt to reconcile their relationship with the firm. From an academic perspective, this is the first study in the marketing literature to examine the downstream effects of firm-induced termination and, in so doing, to apply the concept of rejection to a consumer-based context. From a managerial perspective, the study uncovers many issues associated with the practice of customer relationship termination

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse