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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.

This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).

A qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.

Results highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.

The study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.

Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.

This research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.

This research sought to determine the impact of the management of electronic customer relationships through applying 5IS model on the mental image of Umniah Mobile Network Operator Company’s customers in Amman City. To fulfill the goals of the study, the researcher adopted the descriptive, analytic method. He developed an instrument to collect the data through a questionnaire, which was distributed through the simple, random sampling method over 700 customers of Umniah Company, in the City of Amman, out of which 400 analyzable questionnaires were retrieved. The researcher further employed the convenient statistical methods applying SPSS 22 Program for data analysis. The study concluded many results such as there is statistically significant impact at the significance level (α < 0.05) for the administration of consumer relationships through the use of 5IS model on the mental image of the provided services of Umniah Mobile Network Operator Company in Amman city. In this concern, the integration component is the most influential in the mental image with the customers of Umniah Company. Therefore, the study recommended the need Umniah Telecom Company has to search for the best means to positively influence shaping the mental image of its products, especially the means through which it can provide more information about its services.

The purpose of this paper is to investigate how customer relationship management (CRM) implementation affects internal capital allocation efficiency, the efficiency with which a firm allocates its capital across its business segments.

The authors use a statistical regression method to analyze a sample of 801 unique firms in the USA from COMPUSTAT and the Computer Intelligence database. This analysis examines the relation between CRM implementation and internal capital allocation efficiency and identifies the conditions under which firms benefit more from CRM implementation. They also use instrumental variables (IVs) to address endogenous concerns with a two-stage least squares (2SLS) model.

The authors find that CRM implementation is positively related to internal capital allocation efficiency. The results are robust to the 2SLS analysis with IVs. This positive relation is more pronounced for firms with effective internal control and for those operating in highly competitive markets.

The research implies that that CRM can have a significant cross-functional effect on corporate financing and budgeting. This also suggests that when chief marketing officers plan marketing initiatives and implement CRM, they should communicate to chief financial officers not only the direct effect but also the indirect strategic benefits of such initiatives to a firm.

The authors reveal a previously overlooked aspect of marketing accountability by suggesting marketing’s impact on internal capital markets. They also enrich the body of literature on CRM benefits by showing a cross-functional benefit from marketing to finance (or capital allocation).

Big data marketing analytics (BDMA) has been discovered to be a key contributing factor to developing necessary marketing capabilities. This research aims to investigate the impact of the technology and information quality of BDMA on the critical marketing capabilities by differentiating between firms with low and high perceived market performance.

The responses were collected from marketing professionals familiar with BDMA in North America (N = 236). The analysis was done with partial least squares-structural equation modelling (PLS-SEM).

The results indicated positive and significant relationships between the information and technology quality as exogenous constructs and the endogenous constructs of the marketing capabilities of marketing planning, implementation and customer relationship management (CRM) with mainly moderate effect sizes. Differences in the path coefficients in the structural model were detected between firms with low and high perceived market performance.

This research indicates the critical role of technology and information quality in developing marketing capabilities. The study discovered heterogeneity in the sample population when using the low and high perceived market performance as the source of potential heterogeneity, the presence of which would likely cause a threat to the validity of the results in case heterogeneity is not considered. Thus, this research builds on previous research by considering this issue.

This paper aims to (1) identify the different performance drivers (lead indicators) and outcome measures (lag indicators) investigated in the literature concerning the four balanced scorecard (BSC) perspectives in operations management (OM) contexts and (2) understand how performance drivers and outcome measures (and substantiated perspectives) are related.

We undertake a systematic literature review of the BSC literature in OM journals. From the final sample of 40 articles, performance drivers and outcome measures have been identified, and the relationships amongst them have been synthesised according to the system dynamics approach.

Findings show (1) the most relevant performance drivers and outcome measures within each BSC perspective, (2) their relationships, (3) how the perspectives are linked through the performance drivers and outcome measures and (4) how the different measures relate systemically. Accordingly, four causal loops amongst identified measures have been built, which – jointly considered – allowed for the creation of a dynamic strategy map for OM.

This study is the first one that provides a comprehensive and holistic view of how the different performance drivers and outcome measures within and between the four BSC perspectives in OM relate systemically, increasing the knowledge and understanding of scholars and practitioners.

This study aims to predict customer churn in resort hotels by calculating the churn probability of repeat customers for future stays in the same hotel brand.

Based on the recency, frequency, monetary (RFM) paradigm, random forest and logistic regression supervised machine learning algorithms were used to predict churn behavior. The model with superior performance was used to detect potential churners and generate a priority matrix.

The random forest algorithm showed a higher prediction performance with an 80% accuracy rate. The most important variables were RFM-based, followed by hotel sector-specific variables such as market, season, accompaniers and booker. Some managerial strategies were proposed to retain future churners, clustered as “hesitant,” “economy,” “alternative seeker,” and “opportunity chaser” customer groups.

This study contributes to the theoretical understanding of customer behavior in the hospitality industry and provides valuable insight for hotel practitioners by demonstrating the methods that facilitate the identification of potential churners and their characteristics.

Most customer retention studies in hospitality either concentrate on the antecedents of retention or customers’ revisit intentions using traditional methods. Taking a unique place within the literature, this study conducts churn prediction analysis for repeat hotel customers by opening a new area for inquiry in hospitality studies.

This study aims to analyze and discuss the impact of corporate social responsibility (CSR) on firms’ performance, as well as to examine the interplay between CSR and the economy, society and innovation.

This paper collects data from 420 manufacturing firms across various geographical regions in China. By using a structural equation model, the paper investigates the impact of CSR on enterprise innovation, customer management capability, market competitiveness (MC) and firm financial performance.

The findings demonstrate that CSR performance positively contributes to enhancing the level of enterprise innovation, as well as customer management capability and market competitiveness. Furthermore, it assists enterprises in improving market competitiveness and elevating customer management capabilities. Thus, CSR can have a positive effect on the firm financial performance.

The outcomes presented in this paper offer valuable evidence regarding the influence of implementing CSR on different aspects of enterprise performance and innovation. Moreover, it provides practical recommendations for enterprises seeking to transition towards low-carbon practices and upgrade their manufacturing industry.

Few studies have conceptualized how companies can build and nurture international dynamic marketing capabilities (IDMCs) by implementing growth hacking strategies. This paper conceptualizes growth hacking, a managerial-born process to embed a data-driven mind-set in marketing decision-making that combines big-data analysis and continuous learning, allowing companies to adapt their dynamic capabilities to the ever-shifting international competitive arenas.

Given the scarcity of studies on growth hacking, this paper conceptualizes this managerial-born concept through the double theoretical lenses of IDMCs and information technology (IT) literature.

The authors put forward research propositions concerning the four phases of growth hacking and the related capabilities and routines developed by companies to deal with international markets. Additional novel propositions are also developed based on the three critical dimensions of growth hacking: big data analytics, digital marketing and coding and automation.

Lack of prior conceptualization as well as the scant literature makes this study liable to some limitations. However, the propositions developed should encourage researchers to develop both empirical and theoretical studies on this managerial-born concept.

This study develops a detailed compendium for managers who want to implement growth hacking within their companies but have failed to identify the necessary capabilities and resources.

The study presents a theoretical approach and develops a set of propositions on a novel phenomenon, observed mainly in managerial practice. Hence, this study could stimulate researchers to deepen the phenomenon and empirically validate the propositions.

This article investigates the practical implementation of the ecosystem approach in different branches of public management within an urban context. It explores how ecosystem thinking is introduced, disseminated and applied in a local government organization.

We utilize a qualitative case study methodology, relying on official documents and expert interviews. Our study focuses on the city of Espoo, Finland, which has actively embraced ecosystem thinking as a fundamental framework for its organizational development for almost a decade.

The case of Espoo highlights elements that have not been commonly attributed to the ecosystem approach in the public sector. These elements include (1) the significance of complementary services, (2) the existence of both collaborative and competitive relationships among actors in public service ecosystems and (3) the utilization of digital platforms for resource orchestration. Our study also emphasizes the need for an incremental adoption of ecosystem thinking in organizational contexts to enable its successful implementation.

The study provides valuable insights into the introduction and dissemination of ecosystem thinking in public management. It also further develops previously developed hypotheses regarding public service ecosystems.