پیش خرید سیستم در خدمات B2B  Antecedents of system purchasing in B2B services

1. Introduction This article aims to analyze the relation between business-tobusiness (B2B) service integration and purchasing strategies and to provide new knowledge on the antecedents of complex purchasing systems. We present the results of an empirical study in the infrastructure management sector (i.e., electricity and telecom networks), in which integrating business services is a current concern among network operators. In this article, we compare the influence of operational services and strategic services on the B2B relationships between service providers and customers. The objective is to contribute to the theories of purchasing strategy of complex solutions, which include bundled products and services (Wise and Baumgartner, 1999). We approach the topic via operational and strategic services, which are defined by the time of customer involvement, stage of modularity, and degree of customisation (de Blok et al., 2010). This study creates a linkage between the need for integrated bundles, co-creation of value, system purchasing strategy, and expected quality of services (Aarikka-Stenroos and Jaakkola, 2012; Ancarani and Capaldo, 2005; Epp and Price, 2011; Tuli et al., 2007; Vargo et al., 2008). With integrated service concepts recently emerging in the industry, we selected infrastructure management services as the focus of the article. The need to adopt such services among the operators of energy networks, particularly in distribution systems, arises from the fact that infrastructure-related functionality and quality requirements significantly increase the importance of effectively managing the interdependence among service activities in the future. The main driving forces are modern societies’ increasing dependence on reliable energy distribution and policy goals aimed at adopting microgeneration as a part of smart energy grids. Trends drive the demand flexibility of energy distribution, the ability to connect small-scale production to the distribution network, and the advanced metering services provided to customers; these increase the complexity of networks and challenge incumbent organizations to further develop their practices (Apajalahti et al., 2015; Hall and Roelich, 2016). The emergence of local micro grid business models will challenge the current centralized monopoly business. In the new business, specialized local energy actors link geographically proximate distributed energy resources, distributed generation, and local consumption or storage, which provide neighborhood-level demand response (Hall and Roelich, 2016; Ruester et al., 2014). The open questions in the energy distribution sector are not limited only to technological infrastructure, which enables the operation of new processes in the customer interface. The energy industry will be in the ferment stage until a consensus is reached on the division of tasks of distribution network operators and on the ownership and management of new resources, including metering equipment or data handling (Ruester et al., 2014). The issues in the business concepts in the renewing industry are related to the proper design and maintenance challenges of distributed generation and smart metering, as well as to the design of demand control services (Colak et al., 2016). New business concepts and technology will change relationships within value networks and thus drive the development of cooperative businesses through partnerships among firms (Apajalahti et al., 2015; Niesten and Alkemade, 2016; Stone and Ozimek, 2010). Joint development activities also increase diversification of the purchasing strategies among distribution network operators because the service requirements differ, and a single standard forpurchasing no longer exists. Therefore, service providers must be aware of the most appropriate customer relation modes to use in order to provide the best value for customers and enhance competitiveness. This is related to the objective of the study to assess the purchasing behavior of network operators with regard to the two types of services purchasing no longer exists. Therefore, service providers must be aware of the most appropriate customer relation modes to use in order to provide the best value for customers and enhance competitiveness. This is related to the objective of the study to assess the purchasing behavior of network operators with regard to the two types of services. The theory of service integration is based on creating value in industrial services and customer–supplier relationships in supply chains. In the industrial context, services are processes that integrate internal and external capabilities to co-create value in collaboration with another party (Aarikka-Stenroos and Jaakkola, 2012; Ulaga and Chacour, 2001). The concept of system purchasing designates the type of buying behavior in which the purchased services are treated as interconnected product–service systems that solve some strategic problem in ways that add value rather than entail costs (Epp and Price, 2011; Caldwell, Roehrich and Davies, 2009). System purchasing seeks new value by procuring such service solutions, in which the provider is integrating multiple service elements as an integrated solution that fits the customer’s problem domain. The system approach in purchase management increases the importance of the relational view in service provision and highlights the service provider’s capability to fit their service models to the customer’s problem domains (AarikkaStenroos and Jaakkola, 2012; Tuli et al., 2007). Despite the wide range of literature on service business models, empirical studies that focus on the factors that lead to system purchasing in B2B services are lacking. To address this recognized gap, our research question is, “How does service integration influence the relationship between the actors and the goals of supply management? ”. For our sample, we selected the customer base of a service provider for IT networks and energy infrastructure. The study was carried out with a web-based questionnaire sent to the service provider’s customers. The sample size was N¼864, and we received responses from 18% of the target firms. The effective sample of customers consisted of 143 valid responses. The research model was analyzed using partial least squares (PLS) path modelling with nonparametric bootstrapping to compensate for non-normality and a low sample size (Henseler et al., 2009). We applied SmartPLS 2.0 software for the data analysis.