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The paper provides an overview of research published in the innovation and operations management (IOM) literature on 15 methods for cost management in new product development, and it provides a comparison to an earlier review of the management accounting (MA) literature (Wouters & Morales, 2014).

This structured literature search covers papers published in 23 journals in IOM in the period 1990–2014.

The search yielded a sample of 208 unique papers with 275 results (one paper could refer to multiple cost management methods). The top 3 methods are modular design, component commonality, and product platforms, with 115 results (42%) together. In the MA literature, these three methods accounted for 29%, but target costing was the most researched cost management method by far (26%). Simulation is the most frequently used research method in the IOM literature, whereas this was averagely used in the MA literature; qualitative studies were the most frequently used research method in the MA literature, whereas this was averagely used in the IOM literature. We found a lot of papers presenting practical approaches or decision models as a further development of a particular cost management method, which is a clear difference from the MA literature.

This review focused on the same cost management methods, and future research could also consider other cost management methods which are likely to be more important in the IOM literature compared to the MA literature. Future research could also investigate innovative cost management practices in more detail through longitudinal case studies.

This review of research on methods for cost management published outside the MA literature provides an overview for MA researchers. It highlights key differences between both literatures in their research of the same cost management methods.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

Disturbing increase in the use of virgin resources to produce new products has threatened the environment. Many countries have reacted to this situation through regulations which aim to eliminate negative impact of products on the environment shaping the concept of environmentally conscious manufacturing and product recovery (ECMPRO). The first crucial and the most time-consuming step of product recovery is disassembly. The best productivity rate is achieved via a disassembly line in an automated disassembly process. In this chapter, we consider a sequence-dependent disassembly line balancing problem (SDDLBP) with multiple objectives that is concerned with the assignment of disassembly tasks to a set of ordered disassembly workstations while satisfying the disassembly precedence constraints and optimizing the effectiveness of several measures considering sequence-dependent time increments among disassembly tasks. Due to the high complexity of the SDDLBP, there is currently no known way to optimally solve even moderately sized instances of the problem. Therefore, an efficient methodology based on the simulated annealing (SA) is proposed to solve the SDDLBP. Case scenarios are considered and comparisons with ant colony optimization (ACO), particle swarm optimization (PSO), river formation dynamics (RFD), and tabu search (TS) approaches are provided to demonstrate the superior functionality of the proposed algorithm.

There have been significant developments in the field of retailing with digitalization. One of these developments is the emergence of omnichannel retailing. Although this has affected both firms and consumers considerably, the literature is dominated by the studies dealing with omnichannel retailing from the firms’ perspectives. The studies dealing with omnichannel retailing from the consumers’ perspectives have recently begun to attract the attention of researchers. For this reason, this study conducted a literature review to examine various consumer behaviors mentioned in the studies aimed at explaining consumer behaviors in the omnichannel retailing context. The distribution of these studies according to years and journals, research methods used, theories adopted, and the related five-stage consumer decision-making stages are summarized. Additionally, this review addresses future research avenues.

This chapter studies the integration of quantitative and qualitative attributes of a particular issue in the strategic “designing” level of the reverse supply chain (RSC) process in a multicriteria decision-making environment. The study employs an analytical network process (ANP) to determine the performance indices of the collection centers derived through qualitative criteria from the remanufacturing facilities that are interested in buying used products. The evaluating criteria are comprised as a four-level hierarchy: the first level contains the objective of evaluating the collection centers, the second level involves the main evaluation criteria taken from the perspective of a remanufacturing facility, the third level contains the subcriteria under the main evaluation criteria, and the fourth level has the collection centers. ANP is presented herein as a matrix that comprises a list of all facets listed horizontally and vertically. This particular method is of value when key elements of a decision are difficult to quantify and contrast, and thus the identification of important facets and their incorporation into a linear physical programing (LPP) environment is of value. To determine the quality of end-of-life (EOL) products for transport from collection centers to remanufacturing facilities, a physical programming approach is adopted. Four criteria and their satisfaction are focused upon: (1) maximizing the total value of purchase; (2) minimizing the total cost of transportation; (3) minimizing the disposal cost; and (4) minimizing the purchase cost. A numerical example is considered in which three collection center locations are evaluated to identify the optimal collection center.

Digitalisation has become a central theme in the current economic and policy debate. Large digital and tech multinational enterprises (MNEs) are gaining an outsized role in the global economy. Also, the adoption of advanced digital technologies across all industries is fundamentally changing production processes. Both these (interrelated) phenomena have profound implications for economic structures, employment, inequality and development and industrialisation opportunities. This chapter analyses the international production and investment (i.e., foreign direct investment [FDI]) implications of the digital economy. First, it empirically documents significant differences in internationalisation patterns between the largest digital MNEs and traditional MNEs; particularly, the tendency of digital MNEs to exhibit an asset-light international footprint. Second, it argues that the powerful transformational forces related to digital adoption and the new industrial revolution have the potential to change international production more broadly, favouring a shift towards internationalisation models characterised by decentralised production, accelerated servicification and extended disintermediation. The chapter concludes with investment policy implications and a number of questions for future research.

Introduction: Micro, small, and medium enterprises (MSME) have long been viable in the Indian economy. In the case of post-COVID-19, 20–40% of MSMEs in government can be permanently closed. The state should pay special attention to MSMEs for survival (Min, 2023).

Purpose: This chapter provides a framework for MSMEs to study industry challenges in Punjab and to discuss the conceptual framework and road map for future MSMEs in Punjab.

Need for This Study: The COVID-19 pandemic has drastically impacted the variable economic activities within the world. This study is responsible for explaining the different vulnerable sectors related to small- and medium-sized enterprises. On the other hand, this study is an analytical and descriptive research in nature.

Methodology: A mixed method of data collection has been used in this chapter. The data have been collected by floating a questionnaire to the various entrepreneurs of MSMEs. Secondary data have been collected through the Internet.

Findings: Through this research, we could analyse the MSMEs’ conceptual framework, the challenges they face, and the industrial units’ future roadmap.

Practical Implications: This research is mainly considered a clear explanation of current competition and market access challenges that small- and medium-sized enterprises face. This situation is derived due to the COVID-19 pandemic, so many enterprises are trying to find their exit ways. On the other hand, some MSMEs are trying to focus on the online business market to make some profit and to overcome the loss.

Entrepreneurship is one of the economic support systems that promote economic growth in Indonesia. Indonesia as a country with good tourism spots has enormous potential to create jobs. The greater the job opportunity, the lower the unemployment. The purpose of this study is to analyze the characteristics of entrepreneurs in the tourism industry in Indonesia. Meanwhile, the method used is a quantitative descriptive approach with logit regression method where four variables are found, namely entrepreneurship, location, gender, and marital status which have a significant positive relationship with the tourism industry. But on the other hand, the location variable also has a significant negative effect on the tourism industry. This study can contribute to government policies to improve Indonesia’s economic development by increasing the productivity of human resources in the tourism industry.