Innovation and Big Data in Smart Service Systems

As traditionally measured, services, which include everything from transportation to retail to healthcare to entertainment to hospitality and more, account for most economic activity. Taking a more modern view, we define service as value creation that occurs within systems of interacting economic actors. Service systems have been getting smarter over time, as big data analytics have been used to generate information and automate operations that create ever more value for people in the service systems. In this short letter, we describe some of our perspective on the use of big data analytics in smart service systems, suggesting one framework for thinking about big data in this context and outlining a set of research issues.ope

IT-Enabled Information-Intensive Services

In information-intensive services (IISs), information interactions have a significant effect on service-value creation. Recent innovations in IT have facilitated the creation of various types of IT-enabled IISs (IT-IIS) in which IT is essential for information interactions. The authors introduce the generic composition of the IIS value-creation system, then view this system from an IT-oriented perspective to propose classifications for various IT-IIS types. This knowledge serves as a basis for designing new IT-IISs. The authors also conducted two IT-IIS design case studies.ope

Applications of Energy Usage Data: A Literature Review

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Scales for Measuring Mobile Service Quality (M-SQ): A Literature Review and Identification of Key Dimensions

Mobile service quality (m-SQ) is vital to manage the competitiveness of a company in the mobile business market. Existing studies on m-SQ share key characteristics of m-service in general, such as mobility and context awareness. A set of common m-SQ dimensions that reflects such key characteristics would serve as the theoretical backbone of m-SQ. This research aims to conduct a comprehensive review of existing studies on m-SQ scales and identify key dimensions of m-SQ to understand the essence of m-SQ scales. A total of 45 existing studies on m-SQ scales were reviewed and seven key dimensions of m-SQ scales were identified. This study is expected to serve as a solid knowledge base for conducting new investigations on m-SQ scale development as well as help practitioners utilize m-SQ scales.ope

Scales for Measuring Mobile Service Quality (M-SQ): A Literature Review and Identification of Key Dimensions

Mobile service quality (m-SQ) is vital to manage the competitiveness of a company in the mobile business market. Existing studies on m-SQ share key characteristics of m-service in general, such as mobility and context awareness. A set of common m-SQ dimensions that reflects such key characteristics would serve as the theoretical backbone of m-SQ. This research aims to conduct a comprehensive review of existing studies on m-SQ scales and identify key dimensions of m-SQ to understand the essence of m-SQ scales. A total of 45 existing studies on m-SQ scales were reviewed and seven key dimensions of m-SQ scales were identified. This study is expected to serve as a solid knowledge-base for conducting new investigations on m-SQ scale development as well as help practitioners utilise m-SQ scales.110Nscopu

PSS Board: a structured tool for product-service system process visualization

The product-service system (PSS) is a system in which its integrated products and services jointly fulfill customer needs. The current research proposes a structured tool called the PSS Board to visualize the PSS process. This is a matrix board where the customer activities, state of the products, services, dedicated infrastructures, and partners are placed in rows, and the general PSS process steps are placed in columns. The visualized PSS on the board shows how the PSS provider and its partners aid customers' job execution process. Previous PSS cases are visualized based on the proposed PSS Board; the utility of the PSS Board is also identified. The current research can serve as an effective basis to analyze PSS from the perspective of fulfilling customer needs, thus supporting companies in diagnosing and elaborating their respective PSSs.ope

A Concept Generation Support System for Product-Service System Development

A product-service system (PSS) is a novel type of business model that integrates products and services in a single system. It provides a strategic alternative to product-oriented economic growth and price-based competition in the global market. This research proposes a methodology to support the generation of innovative PSS concepts, called the PSS concept generation support system. The models and strategies of 118 existing PSS cases were analyzed, and the insights extracted were used to develop the methodology. The methodology consists of various tools and a systematic procedure to support the generation process. It is generic enough to be applied to a variety of PSS contexts. The methodology is demonstrated and verified via case studies on the washing machine and refrigerator industries. The proposed PSS concept generation support system can serve as an efficient and effective aid to PSS designers for new PSS development.ope

System Informatics-based Services: Recent Cases and Research Issues

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Accelerated whole breast irradiation in early breast cancer patients with adverse prognostic features

Purpose: Accelerated whole breast irradiation (AWBI) and conventional whole breast irradiation (CWBI) were compared to determine whether AWBI is as effective as CWBI in patients with early breast cancer and adverse prognostic features. Patients and methods: We included 330 patients who underwent breast-conserving surgery (BCS) and post-operative radiation therapy (RT) using AWBI for pT1-2 and pN0-1a breast cancer from 2007 to 2010. These patients were matched with 330 patients who received CWBI according to stage, age (+/- 3 years), and the year of BCS. AWBI of 39 Gy and CWBI of 50.4 Gy were given in 13 and 28 fractions, respectively. Results: Median follow-up time was 81.9 months. There were no statistically significant differences between the AWBI and CWBI groups in terms of age, stage, tumor grade, or molecular subtype. More patients with Ki-67 index >= 14% were present in the AWBI group (AWBI 47.0% vs. CWBI 10.3%; P= 14% was marginally related to IBTR (5-year IBTR rate: 2.2%; P=0.07). There were no statistically significant differences in the hazard ratios between the AWBI and CWBI groups according to any of the risk factors. There were no acute grade 3 toxicities in the AWBI group. There were no late grade 3 toxicities in either group. Conclusions: AWBI is comparable to CWBI in early breast cancer with adverse prognostic features