Customer Resource Research Articles

Determination of the main design parameters of cost-effective remote sensing satellite systems at the stage of preliminary design

This article surveys approaches to the selection of design parameters and modelling the functioning of the remote sensing satellite systems, taking into account the requirements and restrictions on customer resources. The objective of this research is to increase the efficiency of the use of space systems to solve urgent tasks of monitoring the earth’s surface. Firstly, an analysis of the requirements for space imagery materials and consumer information support was carried out, secondly, mathematical models of remote sensing equipment and onboard systems of small spacecraft were developed, and finally, a database with the technical characteristics of the onboard systems and remote sensing equipment of spacecraft, launch vehicles and ground-based reception and processing information facilities was created. As a result, software to determine main design parameters and modelling the functioning of cost-effective remote sensing satellite systems was developed.

Analysis and Research on the maturity of electricity retail market

On the basis of interpreting the policy of “new electricity reform”, this paper defines the maturity level of electricity sales market after new electricity reform in China from five dimensions: potential market, emerging market, initial development market, semi-mature market and mature market. With the development of electricity sales market, the evaluation methods of customer resource value are gradually improved, and different maturity periods of electricity sales market have different influences on customer value evaluation.

Analysis of the construction of a marketing system based on customer relationship management

In an increasingly competitive market, if companies can accumulate customer resources, they can make this part of their core competencies a key point. When making purchasing decisions, customers are not only concerned about product quality and price, but also about psychological satisfaction and service satisfaction during the purchase process. Analysing customer relationship management based on the consumer's perspective can help to meet the psychological needs of different customer groups according to their purchasing characteristics and strengthen customer loyalty to the brand to complete the long-term use of resources.

Mapping of Journal of Service Research Themes: A 22-Year Review

The Journal of Service Research ( JSR) is one of the leading outlets in service research. It is international in scope and widely recognized among scholars, academicians, and practitioners for its original and well-executed research. In its 22 years of publishing, the journal has produced literary content considered classics in the service domain. With the application of bibliometric techniques, we examine articles published in JSR between 1998 and 2019. Our study explicates JSR’s prominent topics and tracks the evolution of research themes in the journal. “Customer satisfaction,” “service recovery,” and “service quality” are some of the prolific themes trending in JSR, while “big data,” “value cocreation,” “customer resource integration,” “service design,” and “customer participation” are its hottest topics. This study contributes primarily by providing a rich retrospective of JSR’s 22 years of publishing and proposes future research topics for the journal.

A Virtualized Target Queuing Balanced Model Using Vmax/M/G-Load(Min)/Cache-P2λM for Reducing Queuing Time Expectation of Customer Delay Tolerance

Queuing theory is a formal mathematical model of late response arrival of customer waiting in various access services, accepting processes management as a whole field. Often multiple server sorting can be used to estimate the number of servers and service rates be high due too lacking of time, with an average delay sequence in the analysis. Using these sequence models to read more than one sequence during execution approximates system sorting performance. To resolve this problem we modulated the distributed process into Virtualized Target Queuing Balanced Model (VTQBM) using Vmax/M/G-Load (Min)/Cache-P2λM for reducing queuing time expectation of customer delay tolerance. The Virtual Resource queuing System is optimized with fork-join queue by creating single to multimodal service performance using target request load balancer in a shared distribution mode. Sorting the request buffer cache is created based on Customer Request Arrival Rate (CRAR) and resource output preferred to check with target rule waiting in the Load balancer. To improve the use of model complex virtual resource sharing shared with customer arrival to Cache Target Load Allocator (CTLA) on queuing distributed resources, This fork joiner target the service performance to reduce the customer waiting time in queuing and produce outputs can achieve a different parameter input transformation on queuing theory.

The potential of web awareness as a determinant of dually defined customer value

In the conditions of increasing demand barrier, the enterprise's basic capital is customers. From an enterprise point of view, this means the need to create a dual perceived and defined customer value which remains related to market value (income and development potential) and customer resource value (reference, information and cooperative potential). The progressing digitisation process transfers business processes, and thus relationships, into virtual space. We identify customers consumers’ behaviour in virtual space and the goals they connect with participation in relational networks.We believe that the use of the potential of the virtual space in which the customer moves is determined by the awareness of the potential of the web, which is related to its readiness and ability to use it. This factor determining customer value (customer equity) exerts and will exert a significant impact on the process of creating value for the customer in the future, strengthening its position as a partner in the process of creating value.

Engaging Gen Y Customers in Online Brand Communities: A Cross-National Assessment

Abstract Global retail brands find it vital to engage Generation Y (Gen Y) customers through firm-hosted online brand communities (OBCs) for generating actionable insights; this study advances customer engagement (CE) frameworks in this setting. First, we draw on the stimulus–organism–response (S–O–R) theory to introduce OBC website quality (termed OBC-SiteQUAL), alongside brand involvement as a customer resource input, to shape an expanded quadripartite CE conceptualisation. Second, using multi-country data, we test the validity of the OBC-SiteQUAL and CE measurement models, and the theoretical framework. Results indicate that the newly conceived OBC-SiteQUAL construct, underpinned by various web-based cues related to affective elements, brand interaction and customer-to-customer interaction, positively influences CE, whereas brand involvement partially influences CE. Third, we examine how these variables translate to behavioural loyalty outcomes. Empirically, a consistent pattern across the country samples indicates that OBC-SiteQUAL can affect behavioural loyalty by enhancing CE. Thus, we reliably confirm the mediating effect of CE (O) between OBC-SiteQUAL (S) and behavioural loyalty (R). Fourth, we found that the impact of OBC-SiteQUAL and brand involvement on CE differs between younger and older Gen Y consumers. These findings inform the optimisation of precise digital content marketing activities to enhance customer-brand relationships.

How additive manufacturing allows products to absorb variety in use: empirical evidence from the defence industry

The normative assumption holds that a product’s structural and functional elements are fixed pre-production to support manufacturing efficiency. Firms servitizing are faced with delivering resources for customers in context and absorbing contextual variety presents a number of challenges. This paper examines shortcomings of modular design and whether additive manufacturing can efficiently provides high variety that meets emergent user demand. A case study is undertaken, drawing upon design change data and in-depth interviews with industry experts. Findings show that introducing design changes to modular products through life creates complexity in the product architecture and the supply chain. We find that AM can act as a supply chain solution, managing complexity and allowing products and supply chains to efficiently and effectively absorb contextual variety. Existing theory must expand beyond the normative assumption that the physical product is fixed, to include cases where the tangible product can absorb variety to meet the emergent need.

Customer capabilities for solution offerings in business markets

Solutions in business markets aim to solve business customers' organizational problems by providing end-to-end offerings consisting of customized combinations of goods and services along the customers' business processes. While the effective integration of customer resources and processes is key for solution success, prior research predominantly focusses in delineating only those capabilities that provider firms necessitate to offer solutions. Yet, it remains unclear which capabilities customer firms require to develop, deploy, and use solutions effectively and how these capabilities differ across different solution types. This study addresses these gaps by combining a critical literature review on organizational capabilities of business customers with empirical insights gained in 20 in-depth interviews with representatives of provider firms across a wide range of industries. Using the repertory grid method, this study identifies five broader capability sets consisting of 16 organizational customer-firm capabilities and demonstrates their importance for different types of solution offerings. Theoretically, this study advances research on solution capabilities by explicating the nature, composition, and relevance of a portfolio of capabilities that customer firms require to bring into the solution process. Managerially, the results can assist solution providers in evaluating, choosing, and developing their customer base during the solution development and deployment process.

The dark side of AI-powered service interactions: exploring the process of co-destruction from the customer perspective

ABSTRACT Artificial intelligence (AI)-powered chatbots are changing the nature of service interfaces from being human-driven to technology-dominant. As a result, customers are expected to resolve issues themselves before reaching out to customer service representatives, ultimately becoming a central element of service production as co-creators of value. However, AI-powered interactions can also fail, potentially leading to anger, confusion, and customer dissatisfaction. We draw on the value co-creation literature to investigate the process of co-destruction in AI-powered service interactions. We adopt an exploratory approach based on in-depth interviews with 27 customers who have interacted with AI-powered chatbots in customer service settings. We find five antecedents of failed interactions between customers and chatbots: authenticity issues, cognition challenges, affective issues, functionality issues, and integration conflicts. We observe that although customers do accept part of the responsibility for co-destruction, they largely attribute the problems they experience to resource misintegration by service providers. Our findings contribute a better understanding of value co-destruction in AI-powered service settings and provide a richer conceptualization of the link between customer resource loss, attributions of resource loss, and subsequent customer coping strategies. Our findings also offer service managers insights into how to avoid and mitigate value co-destruction in AI service settings.

Online contextual learning with perishable resources allocation

We formulate a novel class of online matching problems with learning. In these problems, randomly arriving customers must be matched to perishable resources so as to maximize a total expected reward. The matching accounts for variations in rewards among different customer–resource pairings. It also accounts for the perishability of the resources. Our work is motivated by a healthcare application, but it can be easily extended to other service applications. Our work belongs to the online resource allocation streams in service systems. We propose the first online algorithm for contextual learning and resource allocation with perishable resources. Our algorithm explores and exploits in distinct interweaving phases. We prove that our algorithm achieves an expected regret per period that increases sub-linearly with the number of planning cycles.

It takes two to tango: The role of customer empathy and resources to improve the efficacy of frontline employee empathy

This study investigates the link between employee empathy and customer satisfaction. Building on social exchange theory, we develop a model of employee-customer empathy. We focus on the central role of customer-oriented behaviour in explaining the empathy-satisfaction relationship, predicting that employee empathy positively influences customer-oriented behaviour, which in turn enhances customer-satisfaction. We also examine the moderating roles of customer empathy, as well as of customer resources. Results of a dyadic-survey study of 211 pairs of frontline employees and their customers support the proposed moderated -mediation model. Theoretical and practical implications are discussed.

Resource integration: Adopting a paradox perspective to inform the management of tensions in customer resource allocation

Service-dominant logic maintains that value is created collaboratively through a process of resource integration. Knowledge-intensive business services, the context for this study, are heavily dependent on customer resources for the fulfilment of the value proposition. Value co-creation is compromised when resources are not allocated in appropriate quality or quantity. While there is a growing body of research identifying antecedents to customer resource input, few studies investigate how customers might overcome barriers to resource allocation, particularly when faced with competing demands. This article uses a paradox perspective to explore the management of tensions affecting resource allocation. Empirically, we draw on interviews with service providers to identify perceived resource deficiencies, and with customers to explore resource allocation management. We show that it is possible to manage resource allocation tensions by devising novel solutions that integrate the two opposing demands. In addition, these solutions can result in an ‘augmented’ resource, particularly if the service provider is permitted to influence customer resource deployment. Finally, these novel solutions can activate an unintended by-product or secondary resource, enhancing the relationship between provider and customer.

The THE CHANGE OF CUSTOMER VALUE AS THE IMPACT OF THE DEVELOPMENT OF MARKET ORIENTATION AND RESOURCES CAPABILITY IN SMALL AGRO BUSINESS: EMPIRICAL STUDY IN EAST JAVA

Small agro business is one type of creative business that can be used as a processed product and is currently being developed by the local municipal government. In general, the national agro commodity has increased but the small agro business are still limited and not widely known by the wider community so that the right strategy is needed in marketing thier product. This research is motivated by the decline in customer trust which can later influence customer value in small agro businesses.
 The purpose of this study was to analyze the effect of market orientation and resource capabilities both partially and simultaneously on customer value and to find out the variables that most influence on customer value in small agro businesses in East Java, represented by two cities, namely Blitar and Bojonegoro.
 This research is descriptive and verificative using explanatory survey, which explains the effect of the independent variable on the dependent variable. The type of data used is primary data and secondary data. The census method is used for the selection of respondent data. Data collection was carried out by means of observation, interviews, and the distribution of questionnaires to 115 respondents of small agro business operators in East Java, represented by Blitar and Bojonegoro.
 Technical analysis of the data is done by normality test, t test, F test, and determination test. The results of the study indicate that market orientation partially influence customer value and resource capability does not affect customer value in small agro businesses in East Java. While simultaneously market orientation and resource capabilities affect customer value in small agro businesses in East Java. Market orientation is the most influential variable on customer value because it has a significance value of 0,000 while resource capability does not affect customer value because it has a significant value of 0.092 exceeding the ideal criteria of 0.05. The better market orientation can create good customer value because it is focused on the customer, be careful in facing competition and establish good coordination between functions.

ConvLSTMConv network: a deep learning approach for sentiment analysis in cloud computing

The rapid development of social media, and special websites with critical reviews of products have created a huge collection of resources for customers all over the world. These data may contain a lot of information including product reviews, predicting market changes, and the polarity of opinions. Machine learning and deep learning algorithms provide the necessary tools for intelligence analysis in these challenges. In current competitive markets, it is essential to understand opinions, and sentiments of reviewers by extracting and analyzing their features. Besides, processing and analyzing this volume of data in the cloud can increase the cost of the system, strongly. Fewer dependencies on expensive hardware, storage space, and related software can be provided through cloud computing and Natural Language Processing (NLP). In our work, we propose an integrated architecture of Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network to identify the polarity of words on the Google cloud and performing computations on Google Colaboratory. Our proposed model based on deep learning algorithms with word embedding technique learns features through a CNN layer, and these features are fed directly into a bidirectional LSTM layer to capture long-term feature dependencies. Then, they can be reused from a CNN layer to provide abstract features before final dense layers. The main goal for this work is to provide an appropriate solution for analyzing sentiments and classification of the opinions into positive and negative classes. Our implementations show that found on the proposed model, the accuracy of more than 89.02% is achievable.

Barriers analysis for customer resource contribution in value co-creation for service industry using interpretive structural modeling

PurposeCo-creating services with the customer has recently appeared as an alternative strategy to achieve competitive advantage. Developing and sustaining a gainful experience requires sharing of knowledge, skills and resources between the firm and its customers. Managing value co-creation throws substantial challenge and difficulties. This study aims to investigate the barriers to customer resource contribution in value co-creation in service industries and find their interrelationships for developing an effective management framework for removal of those barriers.Design/methodology/approachA systematic literature review led to the identification of 26 barriers, which were further confirmed through expert opinion. The study used interpretative structural modeling (ISM) approach and Matrice d’Impacts croises-multipication applique (MICMAC), for analyzing the contextual relationships and develop a hierarchical model of the barriers.FindingsISM approach led to the development of a 13-level structural model. The barriers were further classified into autonomous, driver, linkage and dependent barriers using the MICMAC analysis. The framework offers a means to fulfill the expectations of the customers, thus leading to successful integration of the customer in the value creation process. Removal of the barriers has also been discussed.Practical implicationsThe framework provides a direction and a tool to meet the expectations of the customers and lead to successful integration of the customer.Originality/valueThe study addresses a gap in the literature for the need of a structured framework for managing the value co-creation process in the service industry

The impact of customer resources on customer value in co-creation: the multiple mediating effects

PurposeCo-creating value with customers is important for companies in order to gain a competitive advantage. Based on resource theory and social interaction theory, the purpose of this paper is to explore the customer participation mechanism in co-creating value and test the effects of different types of customer resources and multi-level customer–firm interaction on customer value.Design/methodology/approachData were collected from tourism industry. Hypotheses were tested using structural equation modeling.FindingsThe results indicate that both the customer’s human resource and relationship resource have a significantly positive effect on customers’ utilitarian value and hedonic value through reactive and proactive interactions. Reactive interaction has a full mediating effect on the relationship between relationship resource and proactive interaction, whereas proactive interaction has a full mediating effect on the relationship between reactive interaction and hedonic value.Originality/valueThis study explores the mediating effects of customer–firm interaction between customer resources and customer value. This paper contributes to the understanding of customers’ motivations for, and the processes of, participating in value co-creation.

How Business Intelligence Can Help You to Better Understand Your Customers

Companies can incur heavy losses when customers do not return; therefore, they need to have a better understanding of their customers' behaviors in order to improve service and products. And nowadays, there are multiple resources of customers' data especially with web services, such as websites, chatbots, emails, social media, PoS, ERP, CRM, SCM, therefore, it becomes difficult to collect all this huge data altogether and analyze it manually This paper highlights the role of business intelligence in improving the relationship with the customers, and explores the techniques used to analyze customers' data in order to predict their demands and reach their satisfaction.

Bank customer loyalty under the background of internet finance and multimedia technology

In recent years, Internet finance has developed rapidly in China, and has attracted more and more attention. With the rise of a variety of online payment, the development of traditional commercial banks has been seriously hindered, a large number of customer resources have been lost and reduced customer loyalty. Therefore, this paper studies how to improve customer loyalty in the context of Internet Finance and multimedia technology. First of all, based on multimedia technology and fuzzy concept, this paper designs and implements the bank customer management system based on multimedia technology and fuzzy concept; secondly, it constructs the corresponding evaluation index system, and designs the relevant functions of the system according to the specific needs of customers; finally, the system is implemented by using spring open-source framework system, web, JSP, EAI and database technology. In the test phase, in order to test the performance of the designed customer management system, this paper constructs a test system. Through the customer experience of using the system and the performance of the new and old management system for comparative analysis of satisfaction, analysis of the advantages of this management system.

Determinants of negative customer engagement behaviours

PurposeUnderstanding negative customer engagement is important as it is argued that negative information has a stronger impact on a customer’s brand perception and purchase decision than that of positive information. Hence, this paper aims to propose new determinants of negatively valenced customer engagement, including disengaged and negatively engaged behaviours in a service consumption context and explore under what conditions customers display disengaged or negatively engaged behaviours.Design/methodology/approachThis study incorporates justice theory, expectancy disconfirmation theory and psychology literature to propose determinants of negative customer engagement behaviours.FindingsA conceptual framework is developed that proposes customer perceived justice and negative disconfirmation as determinants of negative customer engagement via the mediator of customer outrage. Moderating variables, include self-esteem, self-efficacy, altruism and vengeance; are also proposed to affect disengaged/negatively engaged behaviours.Originality/valueThis study is the first to specify the underlying reasons of negative customer engagement by establishing the conceptual linkages between negative disconfirmation, justice and negative customer engagement via the mediating role of customer outrage. Further, customer resources are used to understand disengaged/negatively engaged behaviours. In doing so, this study views negative customer engagement from the perspective of a customer’s internal response to the trigger experience, rather than the experience itself. Thus, this study contributes to literature on customer engagement by developing a conceptual framework that illustrates the underlying cognitive and affective responses that drive negative customer engagement behaviours.