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The purpose of this paper is to analyse econometrically determinants of total factor productivity (TFP) in Indian manufacturing plants with a focus on the influence of services input on productivity.

Plant-level data drawn from Annual Survey of Industries for the years 1998-1999 to 2012-2013 are used for the estimation of TFP at plant-level by applying the Levinsohn–Petrin methodology. Econometric models are estimated to explain variations in plant-level TFP. The explanatory variables used are services input intensity (split into manufacturing services purchased and other services), the share of information communication technology (ICT) assets in total fixed capital stock, the share of contract workers in total workers and the share of imported materials out of total materials used, with plant size taken as a control variable. Model estimation is done by applying the fixed effects model.

Econometric results indicate that services input and ICT intensity have a significant positive effect on productivity of manufacturing plants in India. Use of imported materials raises productivity, whereas the use of contract workers in place of regular workers tends to lower productivity. The impact of imported materials on TFP of manufacturing plants seems to be relatively bigger for labour-intensive, low technology industries.

Care has been taken for TFP measurement. Analysis of the impact of services input on TFP has been undertaken for Indian manufacturing using plant-level data for the first time.

The purpose of this paper is to differentiate the production process within services from the dominant manufacturing-based production process, with the objective of delineating the production process in services and highlighting its implication for service productivity.

This study critically reviewed the extant literature on the production processes in manufacturing and services from a multidisciplinary perspective and proposed a framework for the service production process and its relationship with service productivity.

The production process for services differs from the dominant manufacturing-based production process and entails an input, transformation process and outcome dimensions. Therefore, any advancement in services, particularly the conceptualisation and measurement of service productivity, is dependent on the application of a service-specific production process.

The understanding and delineation of the production process in services would further scholarly understanding of what is means to be productive in services and the impact on the validity of the conceptualisation and measurement of service productivity and other service-related concepts.

The proposed service-based production process can further managerial understanding of the measurement and management of productivity in services.

This paper delineates the production process in services and highlighted its implication for service productivity. This study, therefore, is a step forward in developing service-specific concepts and measures, particularly service productivity.

Recognizing the heterogeneity of services, this paper aims to clarify the characteristics of forward and the corresponding reverse supply chains of different services.

The paper develops a two-dimensional typology matrix, representing four main clusters of services according to the degree of input standardization and the degree of output tangibility. Based on this matrix, this paper develops a typology and parsimonious conceptual models illustrating the characteristics of forward and the corresponding reverse supply chains of each cluster of services.

The four main clusters of service supply chains have different characteristics. This provides the basis for the identification, presentation and explanation of the different characteristics of their corresponding reverse service supply chains.

The findings of this research can help future researchers to analyse, map and model forward and reverse service supply chains, and to identify potential research gaps in the area.

The findings of the research can help managers of service firms to gain better visibility of their forward and reverse supply chains, and refine their business models to help extend their reverse/closed-loop activities. Furthermore, the findings can help managers to better optimize their service operations to reduce service gaps and potentially secure new value-adding opportunities.

This paper is the first, to the authors ' knowledge, to conceptualize the basic structure of the forward and reverse service supply chains while dealing with the high level of heterogeneity of services.

Supply chains are quite easy to define for manufacturing organizations where each participant in the chain receives inputs from a set of suppliers, processes those inputs, and delivers them to a distinct set of customers. With service organizations, one of the primary suppliers of process inputs is customers themselves, who provide their bodies, minds, belongings, or information as inputs to the service processes. We refer to this concept of customers being suppliers as “customer‐supplier duality.” The duality implies that service supply chains are bidirectional, which is that production flows in both directions. This article explores the customer‐supplier duality as it pertains to supply chain management, including practical and managerial implications.

eScience workflows use orchestration for integrating and coordinating distributed and heterogeneous scientific resources, which are increasingly exposed as web services. The rate of growth of scientific data makes eScience workflows data‐intensive, challenging existing workflow solutions. Efficient methods of handling large data in scientific workflows based on web services are needed. The purpse of this paper is to address this issue.

In a previous paper the authors proposed Data‐Flow Delegation (DFD) as a means to optimize orchestrated workflow performance, focusing on SOAP web services. To improve the performance further, they propose pipelined data‐flow delegation (PDFD) for web service‐based eScience workflows in this paper, by leveraging from the domain of parallel programming. Briefly, PDFD allows partitioning of large datasets into independent subsets that can be communicated in a pipelined manner.

The results show that the PDFD improves the execution time of the workflow considerably and is capable of handling much larger data than the non‐pipelined approach.

Execution of a web service‐based workflow hampered by the size of data can be facilitated or improved by using services supporting Pipelined Data‐Flow Delegation.

Contributions of this work include the proposed concept of combining pipelining and Data‐Flow Delegation, an XML Schema supporting the PDFD communication between services, and the practical evaluation of the PDFD approach.

The aim of this paper is to understand the antecedents and effects of performance attribution challenges arising in the provision of business-to-business (B2B) services in supply chains.

The study draws on three in-depth case studies of logistics service providers (LSPs) offering supply chain solutions to their clients in Sweden. The analysis of performance attribution challenges and their antecedents and effects is based on 38 semi-structured interviews and review of 43 documents, including contracts and performance monitoring records.

Three key antecedents of performance attribution challenges are stressed. Two of these, the inseparability and contestability of service inputs, are closely related to the notion of service co-production. The third antecedent is the limited provider capability in performance data collection and analysis. Performance attribution challenges may result in provider aversion to performance-related risk and have a harmful effect on client relationships, for example, in terms of provider perceptions of opportunism and unfair allocation of gains. These effects can be mitigated through contracting, interventions in performance measurement system design and deployment of relational mechanisms.

The paper extends the service management literature that emphasises on service co-production by suggesting that inputs of the client firm and its supply chain partners may not only vary in quality but also can be inseparable from provider inputs and highly contestable. It also empirically demonstrates how performance attribution challenges and their antecedents and effects manifest themselves in B2B service provision, as opposed to supply chain settings where the main user of logistics services is the consumer.

LSP managers should contract for performance based on high-quality and incontestable external inputs they rely upon. Contractual specifications (performance indicators and related incentives) should explicate and consider the inputs required by clients and their supply chain partners to minimise their contestability.

The study proposes an empirically based framework of the antecedents and effects of performance attribution challenges, an issue that has received scant attention in logistics outsourcing research and the business services literature more broadly.

The purpose of this paper is to propose a service-dominant (S-D) logic-based input-output analysis approach to systematically measure the effects of technology spillover in the service sector.

This study uses a case to demonstrate the feasibility and contributions of the S-D logic-based input-output analysis approach.

This study adopted the idea of customer involvement to formulate the S-D logic-based input-output analysis approach. Service providers can apply this systematical approach to find potential opportunities to spread information technology and co-create values with customers.

The S-D logic-based input-output analysis approach has elasticity to dynamically employ different perspectives to evaluate the effects of technology spillovers in order for integrity and precision. The proposed approach is to delineate the possible target values that related to specific services based on the notions of operant resources and customer involvement in a selected service sector. Service providers within the service sector have to offer innovative service activities and manage existing services for customers to participate in.

The dynamics of economic growth in India continues to engage economists and still remains much debated. The trends and patterns of growth observed in India have seen acceleration in growth in Indian economy in the period following macroeconomic reforms and policy changes in investment and trade regimes. However, when and how did India transform itself from Hindu rate of growth to the present growth regime continues to be debated.

Using INDIA KLEMS data set, this study provides a distinctive perspective on India’s economic growth. A unique data set comprising 27 sectors of Indian economy at a disaggregate industry level for a period of 30 years, beginning 1980s, attempts to understand the dynamics of India’s growth from the contribution of industries that comprise the Indian economy.

This productivity data set offers a new way of analyzing the dynamics of growth including the sources of growth. The growth empirics allow evaluation of the relative significance of total factor productivity growth vis-a-vis input accumulation in accounting for output growth. In addition, the authors were able to document the industry contributions to aggregate growth. In this way, they were able to analyze the importance of the constituent industries within the different sectors of the economy − agriculture, manufacturing, construction and market, as well as non-market services in accounting for the observed growth in India. In conclusion, the industry perspective offers a new and analytical way of discerning new aspects of India’s march to higher growth regimes in post-1990s era.

A unique data set comprising 27 sectors of Indian economy at a disaggregate industry level for a period of 30 years, beginning 1980s, attempts to understand the dynamics of India’s growth from the contribution of industries that comprise the Indian economy.

The aim of this paper is to analyze and compare the performance of the construction sector in Turkey and selected European Union (EU) countries using input‐output (IO) tables for the years 1998 and 2002.

IO tables are used to analyze and compare the construction sector. First the input‐output analysis and the construction sector are briefly introduced. Then, the data and methodology are specified. A set of indicators obtained from the data is used for the comparative analysis.

The construction sector of the selected 13 countries is examined in terms of Gross National Product (GNP) and National Income (NI) shares; direct and total construction backward and forward linkage indicators and direct and total construction inputs from manufacturing and services reflecting the technologies used in construction. The key findings are pointed out in the conclusion.

The lack of data from Turkey relating to recent years and incompatibility of new and old data limit this study's scope to the two years.

The concept of using IO analysis for comparing the construction sector has been around for a considerable period of time. This paper has an importance for comparing the construction sector in Turkey and some selected EU countries, being the first study in that field in Turkey, and is therefore of direct importance for the Turkish construction sector.