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A quantitative theoretical model is proposed to measure how productivity performance can be affected by strategic decisions related to specific competitive priorities.

This study proposes the Primary Transformation Model (PTM) and an equation to measure cause-and-effect relationships between productivity and competitive priorities.

The interdependence between productivity and competitive priorities was studied using the PTM and the proposed model indicates that strategies that improve external performance also impact internal productivity. It was also observed that the compatibility between competitive priorities depends on the initial manufacturing conditions and the implementation method adopted.

The proposed model is theoretical and, as such, is an abstraction of reality and does not consider all possible aspects. It consists of a novel approach that still requires further empirical testing. The PTM provides insights about the trade-offs between productivity and strategic objectives, as well, contributes to the ongoing research on manufacturing strategy and can be further developed in future studies.

The main practical implication is to allow companies to relate their strategic decisions to their productivity performance.

This research also contributes to societal issues by enabling firms to better align strategic objectives and operations, which ultimately allows offering products more suited to the needs of customers, thus making better use of the required resources and favoring economic growth.

The model proposed allows objective assessment of actions aiming at operational efficiency and effectiveness, in addition to providing insights into cause-and-effect relationships between productivity and competitive priorities. The model can also be used in empirical investigations on manufacturing strategy.

This paper aims to discuss the firm productivity premium for servitized firms. It discusses servitization across the product value chain and estimates the effects of the range and extent of servitization on productivity premium in manufacturing firms.

This paper develops a conceptual framework and tests the hypotheses on the effects of servitization on productivity premium using linear regression models with a sample of 20,837 Russian manufacturing firms gathered from the Ruslana Bureau van Dijk database and the Russian customs service.

Servitized firms exhibit higher total factor productivity and labor productivity. The labor productivity premium increases with the number of services offered. However, the impact of services on productivity varies along the product value chain: postmanufacturing and postsales services enhance productivity premium, while manufacturing and back-office services diminish them. The effect of establishment services remains ambiguous.

This paper offers an analytical framework for firms to assess their servitization strategies. These strategies should be gradual, focused on enhancing firm efficiency rather than being an end goal. Firms should initiate the process by introducing services at the postproduction and postsales stages of the product creation chain to achieve productivity premium.

The paper extends the evidence on firm-level productivity drivers and contributes to the servitization theory. A servitization strategy should be portfolio-based, considering both the potential gains and losses in productivity resulting from the implementation of specific services.

This study investigates the optimum size for manufacturing firms and the impact of subcontracting on firms' likelihood of achieving their optimal scale in Vietnam.

Using data from the enterprise census in 2017 and 2021, the paper first estimates the production function to identify the optimum firm size for manufacturing firms and then, applies the logit model to investigate factors associated with the optimal firm size.

The study reveals that medium-sized firms exhibit the highest level of productivity. Nevertheless, a consistent trend emerges, indicating that nearly 90% of manufacturing firms in Vietnam operated below their optimal scale in both 2017 and 2021. An analysis of the impact of subcontracting on firms' likelihood to achieve their optimal scale emphasizes its crucial role, especially for foreign firms, exerting an influence nearly five times greater than that of the judiciary system.

The paper's findings offer crucial policy implications, suggesting that initiatives aimed at enhancing the overall productivity of the manufacturing sector should prioritise facilitating contract arrangements to encourage firms to reach their optimal size. These insights are also valuable for other countries with comparable firm size distributions.

This paper provides the first empirical evidence on the relationship between firm size and productivity as well as the role of subcontracting in firms' ability to reach their optimal scale in a country with a right-skewed distribution of firm sizes.

This study examines the performance of India's food processing sector by estimating its output growth, technical efficiency (TE) and input-driven growth (IDG)

This study used panel data from six food processing manufacturing industries for the period 2000–01 to 2017–18. Technical efficiency and input-driven growth was measured using the parametric half-normal stochastic frontier production function.

The findings of this study showed that the estimated average technical efficiency is 86.6%, which specifies that the Indian food processing sector is technically inefficient. In addition, the output growth rate is 5.5%, driven by high doses of inputs (5.7%), whereas there is no indication of constant returns to scale. However, the food processing sector has experienced more input-driven expansion than either technological or efficiency changes.

This study is limited to India's organized manufacturing food processing sector; the aggregate macro data at a three-digit level based on the national industrial classification (NIC) was used. This study provides robust estimates for industrialists and processors, as well as concrete policy formulations on how overdoses of inputs may lead to high exploitation of resources, whereas outputs can be augmented by implementing upgraded and new technologies.

Previous research has estimated the total factor productivity and technical efficiency only in order to analyze the food sector's performance, but none of the studies have evaluated the share of inputs in growth performance and efficiency. Therefore, this study contributes by measuring growth performance and the share of inputs in the growth performance of India's food processing sector.

The main purpose of this study is to examine the impact of imported inputs on firms' productivity in selected South Asian economies, namely Pakistan, India and Bangladesh. Furthermore, this study explores the complementarity between firms' capabilities and imported inputs in an augmented productivity framework.

A dataset comprising 7117 manufacturing firms of selected South Asian economies was taken from the World Bank for 2013 and 2014. The empirical analysis was based on stochastic frontier models, the ordinary least square method and instrumental variable estimation techniques.

The empirical results show that imported inputs have positive and significant effects on the firms' productivity in the selected countries. Moreover, the study findings demonstrate that firms' capabilities play a complementary role in expanding the firms' production frontier.

The study outcomes suggest that reducing tariffs on imported inputs will enhance the firms' productivity in the selected emerging economies. However, the study further finds that the potential gain of imported inputs is conditional on the firm's capabilities. It implies that firms operating in these countries can improve their performance by allocating more resources to capabilities, such as workers’ training, management and internal R&D effort.

The existing literature on the subject is sceptical about the positive impact of imported inputs on firms' productivity in the case of developing countries. In this regard, the shortage of skilled labour and firms' capabilities are compelling rationales that need to be explored. Thus, the potential contribution of the study lies in explaining the moderating role of firm's capabilities operating in the selected emerging economies in the nexus of imported inputs and productivity.

Drawing on the resource dependence theory (RDT), this paper investigates ownership composition, export intensity, and industry class as moderating factors to investigate the role of imported raw materials in performance of inward foreign direct investment (IFDI) in Ethiopia.

The hypotheses were tested using secondary data obtained from the 2016 Central Statistical Agency (CSA) on Large- and Medium-Scale Manufacturing and Electricity Industries Survey. The data included basic quantitative information on the country's manufacturing industry. The data items for the 2016 manufacturing and electricity industries surveyed are the numbers of proprietors or establishments involved in various sectors. The report did not record small firms that employed fewer than 10 people and did not use power-driven machinery. Two-Stage least squares (2SLS) regression analysis was performed to test the proposed hypotheses.

The results of this study indicate that three moderators (ownership composition, export intensity, and industry classification) interact with the hypothetical relationships between imported raw materials and performance. These findings enrich the knowledge of IFDI firms' operations in Ethiopia and in other least-developed countries (LDCs). The findings could provide information for IFDI firms that are looking to invest in LDCs.

Like all social science research, this study has some limitations. First, the research was conducted with the data found in the Report on Large- and Medium-Scale Manufacturing and Electricity Industries Survey In 2016. This was the first year of the second five-year Growth and Transformation Plan (GTP II), a national development plan for the 2016–2020 period. Continual research on IFDI in Ethiopia in the following years will be needed to get a full picture of the effects of the determinants on IFDIs.

To IFDI investors, the result of this thesis demonstrates several alternatives to overcoming hurdles in manufacturing operation. The results find that J.V. firms make better use of imported raw materials than W.O. subsidiaries in order to achieve better performance. Concerning the choice between focusing on export or domestic markets, the study suggests that domestic market—oriented companies require less imported raw materials to achieve better performance. Concerning the comparative advantage on different industries, this study found the performance of firms in Industry 12 depended on imported raw materials. These findings highlight the challenges and opportunities for potential foreign investors. Ownership composition, market factors, and industry factors should be well considered in making investment decisions.

This is one of few studies on IFDI in Ethiopia, the most populous LDC. Ownership composition, export intensity, and industry class are used as moderating variables to investigate the difference between imported raw materials and the level of expatriate deployment to IFDI performance. For IFDI investors, the results of this study demonstrate several alternatives to overcoming hurdles in manufacturing operation.

Based on the research of free trade agreements on alleviating service trade policy heterogeneity and its impact on manufacturing exports, this article aims to not only provide a basis for China's strategy of promoting regional economic integration, but also provide a policy reference for the manufacturing industry to expand the export market space.

This study uses the two principles of “answering” and “scoring” to quantify the indicators of service trade policy heterogeneity to test the relationship between heterogeneity of service trade policy, free trade agreement and manufacturing export.

According to empirical study, the export of Chinese manufacturing firms is severely hampered by the variety of service trade regulations, and the bigger the enterprise, the more hampered it is. In comparison to communications, transport and commerce, the financial industry's policy heterogeneity has a greater negative impact on certain industries. The major methods used to reduce the impact of service trade policy heterogeneity on manufacturing exports are product price increases and product quantity reductions. Also, by reducing the heterogeneity of service trade regulations and fostering industrial exports, the free trade agreement that China has signed can be quite successful. The open commitment in the area of national treatment, however, can reduce policy heterogeneity and advance manufacturing.

In the area of market access, the effect of export is superior to the open promise. Thus, in order to effectively support the stabilization of international trade, China should actively encourage the negotiation and signing of higher-quality and mutually beneficial free trade agreements.

The purpose of this study is to dissect the transport infrastructure performance, public spending in transport infrastructure development and the manufacturing sector in determining the transport sector energy consumption.

An analysis of transport energy consumption with the transport infrastructure performance, public spending in transport infrastructure and manufacturing sector output in India using annual data for the period 1987–2019. The study used the autoregressive distributed lag (ARDL) bounds test approach along with FMOLS, DOLS and canonical cointegration regression (CCR) methods.

The results of the ARDL bounds test provide evidence for the long- and short-run relationships among study variables. It evidenced that transport infrastructure performance reduces transport energy consumption by using FMOLS, DOLS and CCR methods. Furthermore, the inference of the positive impact of value added in the manufacturing sector on transport energy consumption validates the higher energy demand of the manufacturing sector from a mobility perspective.

The estimated finding of this study is expected to be contributing to policy-making discussions on transport infrastructure and manufacturing sector development in an emerging economy like India with insights on energy consumption.

To the best of the authors’ knowledge, this is the first study that integrates the impact of manufacturing sector output on transport sector energy consumption along with transport infrastructure performance and public investment in the transport infrastructure.

The purpose of this paper is to report a review of various perspectives of lean in heavy engineering and fabrication industries and to propose a framework.

Lean manufacturing (LM) earlier known as Toyota Production System (TPS) was mainly used by automobile industries where the operations occur in sequence and the adoption of LM was easier. When it comes to heavy engineering industries, the concept of lean can be adopted in a versatile operating environment to have more advantages by waste elimination thereby having higher profit. Thus, an effort is made to consolidate various lean perspectives, namely, barriers, principles, tools and performance measures and a framework was proposed on how various lean perspectives can be adopted in a systematic way.

A comprehensive analysis of lean from various perspectives from viewpoint of the fabrication industry are done and the review is presented. Also, the framework linking barriers, principles, tools and performance measures is being contributed as an outcome of the review.

The review of lean from various perspectives for the fabrication industry and the development of a framework is the original contribution of the authors.

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.