Customer Co-creation through the Lens of Service-dominant Logic: A literature Review

The proliferation of the service sector in the age of big data highlights the role of customers as co-creators for business value. Customer interactions on digital platforms make a significant contribution to the vast amount of big data. Considering the lack of systematic and comprehensive studies on this research stream, the objective of the paper is to conduct a concept-centric literature review on customer co-creation from the lens of the service-dominant logic and guide future research. The paper systematically synthesizes and categorizes 50 articles by the concept matrix to reveal the interrelationships among them. The result of the paper provides a holistic overview of value, resources, and mechanisms relevant to customer co-creation. Concrete ideas for future research directions are also proposed for enriching the academic literature and promoting practical implications. The paper holds important implications for accelerating customer co-creation for service providers to achieve big-data-driven competitive advantages

A Service-based Model for Customer Intelligence in the Age of Big Data

The dominance of the service sector in today’s economy gives prominence to customer intelligence as a means for enterprises to provide optimal service. In fact, the revolution of big data has generated a vast amount of customer data and reshaped the dimensions of science, management, and engineering within enterprises. The big data era also acknowledges the role of customers as value co-creators. Therefore, the objective of this paper is to propose a service-based customer intelligence model, hereafter called SBCI (Service-based Customer Intelligence) model, to guide the development and application of customer intelligence. Laid the groundwork upon the service science, the model is proposed with three levels: i) the network of service systems level for customer value co-creation, ii) the service system level for the science, management, and engineering dimensions, and iii) the service level for customer intelligence services

Context-aware Knowledge-based Systems: A Literature Review

Context awareness systems, a subcategory of intelligent systems, are concerned with suggesting relevant products/services to users' situations as smart services. One key element for improving smart services’ quality is to organize and manipulate contextual data in an appropriate manner to facilitate knowledge generation from these data. In this light, a knowledge-based approach, can be used as a key component in context-aware systems. Context awareness and knowledge-based systems, in fact, have been gaining prominence in their respective domains for decades. However, few studies have focused on how to reconcile the two fields to maximize the benefits of each field. For this reason, the objective of this paper is to present a literature review of how context-aware systems, with a focus on the knowledge-based approach, have recently been conceptualized to promote further research in this area. In the end, the implications and current challenges of the study will be discussed

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Smart Data as a Service

Nowadays, smart data emerge as a new research direction to create value from business data in an intelligent way. Smart data are defined as the data gathered and processed that can be used to create new insights for smart solutions to support business strategies. This paper aims at proposing a conceptual model for smart data management. In other words, the model can be used for designing a smart service system based on the perspective of service science that can manage and deliver smart data as a service

Key Performance Indicators for Crisis-Ready Organizations in the Era of Massive Data: The Case of the Cultural Sector

The COVID-19 pandemic has fueled attention towards strategic decisions on business value, crisis responses, and social aspects. Correspondingly, there is an urgent need for identifying relevant key performance indicators (KPIs) to support the decision-making process and survive from exogenous shocks. The paper focuses on the cultural sector, one of the social and economic sectors that has faced severe disruption by the pandemic. The objective of this study is to conduct a literature review on KPIs, especially for organizations in the cultural sector, with relevance to massive data and crisis response. The research results indicate the novel balanced scorecard covering the perspectives of finance, customers, web, social media, and crisis responses for crisis-ready organizations. The importance and originality of this study are that it updates the traditional balanced scorecard with KPIs in the era of digitalization to remain agile and resilient in the pandemic

Towards Knowledge-based Smart Service Systems: The Case of a Recommender System for a Cultural Organization

Big data and artificial intelligence (AI) lead to a revolution that transforms conventional enterprises into data-driven organizations in which knowledge discovered from big data and processed by AI techniques will be integrated into traditional knowledge in order to provide smart services to business users. Consequently, a major concern is how to design and develop a knowledge-based smart service system for supporting AI-based applications. This paper proposes an approach for elaborating a knowledge-based smart service system and demonstrates the approach with a case study about a knowledge-based smart service system for a cultural organization. The proposed approach includes different layers such as Data-as-a-Service, Information-as-a-Service, Knowledge-as-a-Service, and Insight-as-a-Service

Trivi: A Conceptual Framework for Customer Intelligence Systems for Small and Medium-sized Enterprises

Customer intelligence is considered as insights resulting from the application of business analytic techniques to promote value creation in the era of big data. The paper has developed a conceptual framework for a customer intelligence system with the focus on small and medium-sized enterprises (SMEs). The proposed framework aims at supporting enterprises to identify the right types of customer intelligence, to determine the right data sources and business analytics techniques, and to design their customer intelligence system. To demonstrate the application of the conceptual framework, a system architecture of a typical customer intelligence system, called Trivi, is presented

The Implementation of Integrated Multichannel Services in the Hospitality Sector in Vietnam

The research streams on multichannel integration (MCI) in the hospitality sector recently caught the attention of academics and practitioners. However, knowledge and understanding of integrated multichannel services are still unfamiliar to enterprises, especially small and medium-sized enterprises (SMEs) and enterprises in developing countries like Vietnam. Since this topic is limitedly exploited in the hospitality industry, the paper explores the opportunities and challenges for implementing integrated multichannel services in the hospitality sector in Vietnam based on the service science perspective. In the context of emerging digital technology and changing consumer behaviour today, an exploratory study on integrated multichannel services of hotels was conducted on eight hotel managers, eight online travel agencies (OTA), and sixteen domestic tourists. The results show the variety of channels of hotels can reach customers thanks to integrated multichannel services. However, the current situation of channel integration (between the direct and the indirect channel of the hotel through online travel intermediaries) is currently inconsistent. For this reason, challenges related to integrated services, promotion and price, and information access in the channel integration of the selected hotels have been explored. Since then, several solutions are suggested to accelerate MCI in the hospitality sector to stimulate demand for domestic tourism