Introduction to the special issue on “Technology management in a global context: From enterprise systems to technology disrupting operations and supply chains”
2022; Wiley; Volume: 68; Issue: 6-7 Linguagem: Inglês
10.1002/joom.1216
ISSN1873-1317
AutoresGregory R. Heim, Xiaosong Peng,
Tópico(s)Collaboration in agile enterprises
ResumoTechnology Management (TM) has long held an important place in operations management (OM) literature. Since the 1990s, TM topics have made up a substantial portion of the papers published in Journal of Operations Management (JOM). Today, the speed of development and innovative uses of new technologies across the globe create many new research opportunities and challenges (Heim et al., 2021), motivating the current special issue. TM research often overlaps with other academic research fields (e.g., technology innovation in organization strategy, information technology [IT] in management information systems [MIS]). Yet, TM issues of interest to operations managers tend to differ in focus, detail, time horizon, and scope from the issues examined in those literatures. TM research in JOM usually delves into the within-firm interface between technology and process change as well as the performance impacts of technology on operations (as explained in the TM department's recent editorial [Heim et al., 2021]). Technology concerns the application of resources and skills by humans to achieve specific aims. Burgelman et al. (2003) defined technology as "theoretical and practical knowledge, skills, and artifacts that can be used to develop products and services as well as their production and delivery systems." Along similar lines, Gaimon (2008) defined technology as "the embodiment and deployment of technical and scientific knowledge and discoveries that lead to the creation of goods and services." Changes in technology can lead to substantial changes in the organization and accomplishment of work (Browning, 2020; Heim & Peng, 2010; Jaikumar, 1988). TM1 provides an inclusive term for managerial activities and academic research pertaining to the generation, deployment, and use of technology. Gaimon (2008) suggested the TM field addresses "how to develop, adapt, and exploit technological capabilities to create new or improved products or services to accomplish the strategic goals of an organization." Diverse contemporary technology developments provide many new research contexts and questions, seeding the research questions behind the innovative papers in this Special Issue. This diversity required that we keep an open mind regarding what research topics today reside among the scope of issues for TM research in OM and supply chain management (OM/SCM). The technology used today for process change may come in the form of software codes, hardware, material processing and handling technology, and consumer devices and enterprise applications. With an increasing need for global, real-time integration and coordination of demand and supply, operations managers must continue to evaluate and install new technology configurations to deploy processes that hopefully will accomplish their aims. Ultimately, operations managers are responsible for making sure that the coordinated use of modern technology ensures the intended outcomes of operational systems, whether for local, idiosyncratic needs or global, enterprise needs. Today's operations managers are often actively involved in technology decisions, partnering with top management (and many other stakeholders) during technology selection, installation, and lifecycle decisions. Operations managers must nurture collaborative partnerships to ensure technology evaluation and implementation decisions are aligned with the sourcing and delivery needs of manufacturing and service operations. With the above as context, we offer a collection of what we believe are excellent papers examining contemporary topics related to the special issue's theme of "Technology management in a global context: From enterprise systems to technology disrupting operations and supply chains." We begin by first reviewing JOM's historical contributions to classic TM research themes and acknowledging the corpus of TM literature in JOM to which this SI contributes. This exercise then enables us to offer up initial responses to the questions, "What's missing?" and "What's next?" The editorial is structured as follows. Section 2 discusses TM empirical research achievements to date, focusing on JOM. Section 3 introduces the papers in this special issue, suggests what research may still be missing, and points out where TM research efforts might focus next. Section 4 concludes and thanks the Reviewers and Editors who made this special issue possible. As a prologue for the special issue, we gather existing JOM papers that fall within the historical scope of TM literature. In the early years of JOM (1980s), a focus on emerging technology and its consequences started with research enquiries into technology choice, group technology, and material requirements planning (MRP) systems. This research later transitioned toward impacts of advanced manufacturing technologies (AMTs) and enterprise resource planning (ERP) systems (1990s). Post-2000 research examined implications of internet-based technology implemented then, dramatically affecting modern OM/SCM processes. Overall, JOM authors have made significant contributions to insights about OM/SCM technology and TM roles in OM/SCM. We chose our list of JOM's TM articles to discuss in a structured manner. To identify articles, we performed searches on JOM's Elsevier and Wiley search engine websites2 using terms such as "technology", "technology management", "IT", "information technology", "technology strategy", "technology outsourcing", and terms specifically related to each topic area. We considered whether each suggested paper fit within TM. The articles were subjectively categorized into groups. We synthesize the articles for each group. Still, the following discussion should not be viewed as comprehensive in a scientific sense.3 We simply hope to convey the enormous breadth of TM research insights from JOM as well as provide context for the Special Issue. We next summarize prior TM literature from JOM. We first group JOM's TM studies into classic TM topics about how to make sense of technology, evaluate and select technology, innovate via technology and diffuse technology to users, choose and adopt technology, design/redesign technology, use and react to technology, learn via technology, develop technology, integrate technology, improve firm performance via technology-enabled operations and supply chains, and outsource technology-enabled systems and services. We then group salient JOM TM studies by their technology application focus: manufacturing, service, retail, healthcare, enterprise/inter-enterprise, e-business, and new product/new service technology. We acknowledge papers in JOM often incorporate two or more TM themes, making any categorization of prior papers imprecise. Still, while our classification is by no means perfect, it is illustrative of the topical associations for historical TM papers from JOM. Seminal papers by Gaimon (2008) and Gaimon et al. (2017) suggested lists of TM research topic areas. Table 1 summarizes those works' discussions into categories pertaining to research themes in TM and areas needing research, demonstrating TM researchers possess broad interests about implications of technology for OM/SCM. Table 1 also suggests academic research has focused on several emerging technology issues. Still, readers who keep abreast of modern technology may note that many recent technology developments are absent from Table 1. Technology and competition Technology and the organization Technology strategy Technology change and uncertainty Technology forecasting Threats created by technology innovations Technology and environmental sustainability Technology sense-making Performance measurement Justification of new technology Evidence of credibility and value of emerging technology (e.g., RFID) How to enhance benefits and reduce risks of technology innovation or technology acquisition Technology innovation, diffusion, and transfer Entrepreneurship via technology Intellectual property and patents for technology Dynamics of innovation Creativity and technology innovation Leveraging new technology innovations Technology-enabled social networks' impact on innovation diffusion Managing a firm's resource-based capabilities Management of knowledge capabilities Challenges faced by knowledge-intensive firms Knowledge work and knowledge workers Managing knowledge in radical versus incremental projects Managing knowledge development and knowledge transfer Product technology development versus process technology development Managing single or multiple (i.e. portfolio) development projects Managing technology within and across firm boundaries Technology outsourcing Decisions to acquire external technology or create internal technological capabilities Contractual agreements for technology innovation and technology management Technology outsourcing impacts on innovation A critical baseline issue in TM concerns how humans try to make sense of technology and its impacts. While subtle, sense-making affects how managers can make use of emerging and advanced technology within operations and how researchers will examine technology in academic studies. Throughout JOM's history, editorials and conceptual thought leadership papers capture notions regarding how changes in technology might have substantial impacts on operations. Early editorials motivated TM topics as being of interest to JOM (Meredith, 1995) and technology as driving changes in modern operations (Meredith, 2001; Meredith et al., 2002). Editorials also discussed how advanced technology would change the nature of services and supply chains (Boone & Ganeshan, 2007; Venkatesh, 2013) and professional service work (Harvey, 2016). Meredith (2001) suggested adapting the OM academic field to the technology interests of practitioners. Conceptual TM papers convey authors' sense-making for the switch from a material-processing economy to an information-based services-oriented economy. A JOM Special Issue on evolution of the OM field discussed many salient TM developments (Sprague, 2007), including historical challenges experienced when adopting MRP (Mabert, 2007) and during the evolution from MRP to ERP systems (Jacobs & Weston, 2007). Karmarkar and Apte (2007) conceptualized the nature of emerging information economy products, processes, and supply networks. Empirical TM research papers must develop some means to measure technology. Researchers possess several different options for measuring technologies deployed in organizations: possession or use of technology (0/1); number of technologies (a count); commonality or uniqueness of technologies (weighted indexes); quality or extent of technology use (ordered index); and user perceptions of technologies (perceptual measurement scales). Historically, JOM has not published many studies focused solely on measurement of technology artifacts, perhaps due to the view that scale development, by itself, is not a sufficient academic contribution (Hensley, 1999). TM measurement tasks tend to take place as part of an empirical exercise to examine antecedents and consequences of technology. Early studies that developed measurement scales for AMTs were published outside of JOM (Hensley, 1999). Later JOM studies addressed issues of measuring technology for its benefits, such as during a justification process of group technology software (Wemmerlöv, 1990). Boyer and Pagell (2000) compared survey-based measures common to the areas of competitive priorities and AMT, arguing for refinement and methods improvement. Froehle and Roth (2004) developed a scale for technology-mediated customer contact. Recently, Malikov et al. (2022) developed measurement approaches for evaluating spatial technology differences and their effects upon locational manufacturing operations productivity in China. Measurement approaches in TM research often are inspired by research in MIS or at the interface of MIS and OM/SCM. Devaraj et al. (2007) developed survey instruments to measure eBusiness technology capabilities, supplier information integration, and customer information integration. Sharma et al. (2016) developed weighted indexes of healthcare IT bundle adoption to evaluate hospital OM. TM papers in JOM have examined technology innovation, focusing on managing technology innovation projects and how a technology diffuses to users. Using a chaos theory lens, Jayanthi and Sinha (1998) evaluated innovation processes – balancing between exploitation and exploration – in high-technology manufacturing. They showed this balancing process across time can be characterized as chaotic (in a scientific sense). Stock and Tatikonda (2000) introduced a conceptual typology of inward technology transfer (ITT) at the project level. Fifarek et al. (2008) used insights from the high-tech, rare-earth-element industry to investigate long-term offshoring impacts on technology innovation. Research also studies patterns and drivers of diffusion relevant to TM, such as best practices and quality systems. Sanders (2008) explored patterns of supplier IT use, with specific supply chain coordination activities with buyers. Sodero et al. (2013) developed a framework to investigate drivers and outcomes of open-standard interorganizational information systems (OSIOS). A body of work focuses on diffusion of ISO management standards, studying longitudinal efficacy of implementation timing as compared to competitors (Lo et al., 2013; Naveh & Marcus, 2005; Su et al., 2015) and moderating impacts of technology coherence or breadth (Benner & Veloso, 2008). In a different context, Yoo et al. (2016) evaluated information flow diffusion in social media. TM literature dating to the 1980s investigated decisions related to technology choice and adoption. Early research studied manufacturing technology adoption decisions and how production environment characteristics (e.g., demand, capacity, product mix) affect adoption decisions. Cohen and Halperin (1986) developed a dynamic stochastic model to compute optimal production plans with evaluation of costs and benefits of various technologies, diving into trade-offs associated with TM. Building on this work, Li and Tirupati (1995) analyzed trade-offs between product mix flexibility of integrated technologies and dedicated facilities that focus on a limited range of products, building an investment model to determine an optimal mix of technology and capacity for given service levels. Unit-cost-based analysis enables quick insights of the impact of a new technology on a process. Yet, such analyses can favor incumbent technology, hindering a company's ability to adopt new technology. Realizing this, Morgan and Daniels (2001) developed a model to integrate product mix and technology adoption decisions to determine cost effectiveness of new technology in the automobile industry. This paper modeled expected future benefits of new technology to more accurately predict new technologies' impacts on profit. Later research investigated enterprise technology adoption, often with respect to its antecedents and consequences. With the emergence of internet technology, literature also investigated e-business system adoption, such as internet-based procurement systems and electronic markets. Examining e-business technology from a firm-level view, Johnson et al. (2007) showed how industry context, firm characteristics, and firm strategic resources influence e-business technology adoption. Aligning with this firm-level view of adoption, Liu et al. (2010) investigated how institutional pressure and organizational culture drive manager intention to adopt internet-enabled supply chain management (eSCM) systems. Autry et al. (2010) used the technology acceptance model to analyze how technological turbulence and breadth impact supply chain technology acceptance and adoption. Recent research also started to study consumer facing technology, such as social media adoption and its impacts on OM (Lam et al., 2016). In a healthcare context, Stevens and van Schaik (2020) examined adoption of minimally invasive techniques for complex aortic aneurysm stent technology. During the 1980s, JOM published editorials motivating a need for research on the factory automation of that era (Meredith et al., 1986). By the 1990s, JOM had published many papers on the design and impacts of computer integrated manufacturing (CIM) systems and cellular manufacturing cells via group technology (Greene & Sadowski, 1984; Hyer, 1984; Suresh & Meredith, 1985; Vakharia, 1986; Flynn, 1987; Wemmerlöv, 1990; Ahmed et al., 1991; Burbridge, 1991; DeSouza & Bell, 1991; Garza & Smunt, 1991; Huber & Brown, 1991; Miltenburg & Zhang, 1991; Shafer & Rogers, 1991; Jensen et al., 1996). Related to this literature are manufacturing processes and production line design studies, often using modeling approaches (Lin et al., 1994; Raman & Chhajed, 1995). Other studies considered social or behavioral factors in addition to technical factors in manufacturing process design (Hyer et al., 1999). Process reengineering was a relevant TM topic, especially when implemented in parallel with, or enabled by, new technology (Grover & Malhotra, 1997). OM literature also investigates digital technologies involved in service process design. Service design can often be viewed as a technology design issue; such research also can take on a service OM flavor. Recently, Ta et al. (2018) used a service design perspective to examine how driver ethnicity affects the design of crowdsourced delivery service systems. Technology for product design processes is another major TM topic we review below. Humans (as customers, users, designers, and operators of technology) play integral parts in technology innovation, implementation, and use. TM research has investigated how human factors of a firm's technology adoption process (e.g., teams) impact a firm's end-user usage (Johnson et al., 2007; Small & Yasin, 1997), user satisfaction (Bala, 2013), and customer satisfaction (Queenan et al., 2011). Studies also examined technology system design issues that incorporate moderating human resource considerations (Huber & Brown, 1991; Malhotra et al., 2001). Chen et al. (2015) considered how exogenous technological turbulence can moderate performance impacts of human resource tactics. Studies also considered human factors such as a safety mindset in the context of hazard reducing technological warehouse systems (de Koster et al., 2011), work force training (Sarkis et al., 2010), unintended responses to IT-based employee monitoring (Scott et al., 2021), and cultural influences on technology adoption/implementation (McDermott & Stock, 1999). Knowledge management and learning are classic topics of TM (Argote & Hora, 2017). A large literature in leading OM journals addresses various issues in knowledge management and learning. Central themes include how learning impacts operational performance (Fugate et al., 2009; Liu et al., 2014), how learning affects the development and use of technology (Baumers & Holweg, 2019), and how technology use affects learning (Boone & Ganeshan, 2001). Studies investigate knowledge creation, acquisition, or transfer in technology projects (Chandrasekaran et al., 2012), manufacturing and service facilities (Staats et al., 2011), and supply chains (Zhou et al., 2014). Hora and Klassen (2013) focused on a knowledge acquisition process whereby managers learn from other firms' operational problems and documented losses. Relatedly, Avgerinos et al. (2020) examined how surgery operation failure events promoted learning and affected task execution over time in a European hospital. Recently, Letmathe and Rößler (2022) compared worker learning via emerging digital work instructions versus traditional, paper-based work instructions. They found that animated, interactive, digital work instructions show promise to stimulate learning in agile manufacturing environments. Stevens and van Schaik (2020) examined healthcare team learning when adopting minimally invasive techniques for complex aortic aneurysm stent technology. Managing the development processes of new product or process technology is another classic topic of interest to TM researchers, but also is of great interest to JOM's new Innovation and Project Management Department (see the recent Mishra and Browning (2020) editorial). Unsurprisingly, JOM contains a large body of research on this topic. Studies in this area examine how resources (e.g., people, tools) are organized (e.g., product development team structure) (Tatikonda & Rosenthal, 2000), how development processes (e.g., concurrent engineering) are carried out to develop new technologies (Tan & Vonderembse, 2006; Upton & Kim, 1998), and how development processes are affected by project contexts such as complexity or uncertainty (Bendoly & Swink, 2007; Koufteros et al., 2002; Swink & Song, 2007). Research also investigates how development processes interface with or involve stakeholders, including internal functional areas (e.g., marketing, engineering, or supply chain) and external suppliers or customers (Petersen et al., 2005; Terjesen et al., 2011; Yan & Dooley, 2013). Modern IT integration toolsets make it easier for technology developers to inter-connect IT within and between firms. As such, the concept of technology integration has inspired interest in TM literature. A seminal paper in this area is Frohlich and Westbrook's (2001) arcs of integration paper, which was replicated and extended several times (e.g., Schoenherr & Swink, 2012). Follow-up research examines impacts of supplier integration, internal integration, and downstream demand integration that are not enabled by technology, mostly using perceptual measures. Limiting our discussion to papers focusing on technological integration, we observe several patterns in TM research. Some papers documented key challenges of supply chain integration required to achieve its potential, such as necessary structural changes and enhanced trading partner collaboration (Power & Singh, 2007), or the need for external technology to exhibit appropriate task-technology fit with characteristics of a firm's internal technology (Liu et al., 2016; Stock & Tatikonda, 2008). Harland et al. (2007) focused on challenges of small and medium enterprises (SMEs), as compared to larger firms, when using technology for supply chain integration. Impacts of supply chain integration on firm performance were examined for non-U.S. firms (Liu et al., 2016; Narasimhan & Kim, 2002; Narayanan et al., 2011) and U.S. firms (Boyer & Hult, 2005; Devaraj et al., 2007; Perols et al., 2013). Researchers also explored impacts of technology-enabled supplier integration on customer performance outcomes (Xue et al., 2013). While many studies examined manufacturing integration, works also examined impacts of technology for service system integration (Karwan & Markland, 2006; Oh et al., 2012; Perols et al., 2013; Abdulsalam et al. 2018). Ultimately, research on TM needs to answer questions of how firms can adopt, develop, or use technology to improve performance. Performance effects can be evaluated at different levels, such as individuals, projects, production lines, facilities, or firms. JOM's body of TM literature investigates technology impacts on facility or firm performance (Das & Narasimhan, 2001; Kotha & Swamidass, 2000; Koufteros et al., 2014; Lam et al., 2016; Liu et al., 2016; Mishra et al., 2013; Sanders, 2007; Tracey et al., 1999). Some prior studies employed sector-level data (Shah & Shin, 2007). Research paradigms and methodologies today move toward department-, process-, or transaction-level data analyses. Studies have demonstrated lower/detailed level impacts of technology at the shop floor (Smunt & Watts, 2003), department (Ferrand et al., 2018), project (Stock & Tatikonda, 2000), or stakeholder (Akturk et al., 2018) level, which in turn impact firm-level performance. Studies at granular data levels provide rigorous evidence of TM contributions to firm performance. Outsourcing allows firms to employ technology capabilities of external vendors to accomplish operational tasks. Insourcing/outsourcing and onshoring/offshoring decisions are typically strategic. How firms arrive at these strategic decisions has often been considered beyond the scope of TM in an OM context. Yet, how firms manage outsourcing processes is a relevant TM topic for OM/SCM (Metters, 2008; Mishra et al., 2020). In today's outsourcing environments, IT has become an important enabler for business process outsourcing (Bhalla et al., 2008). Technology outsourcing research examines issues in information systems outsourcing, service outsourcing, and business process outsourcing, among other areas. Metters (2008) proposed a typology to characterize the nature of insourcing/outsourcing and onshoring/offshoring decisions, to help managers decide how and when to take advantage of digitally outsourced services. TM research documents many types of outsourcing that occur via technology, including business processes (Narayanan et al., 2011), technology services (Das & Joshi, 2007), professional services (Ellram et al., 2008; Stratman, 2008), innovation services (Fifarek et al., 2008), and maintenance services (Persona et al., 2007). TM research questions pertain to enablers of outsourcing such as IT (Handley & Benton, 2009; Narayanan et al., 2011; Stratman, 2008), impacts of outsourcing such as its effects on quality or safety (Steven et al., 2014; Mishra et al., 2020), and alignment of outsourcing with organization structure, incentive design, and cultural practices (Samaddar & Kadiyala, 2006). The transaction-based view and the resource-based view provide two major theoretical underpinnings of research on outsourcing in JOM (Holcomb and Hitt, 2007). TM research has been performed across a number or industry and sector contexts. Table 2 summarizes the major research contexts of interest, especially as mentioned in prior TM literature. Table 2 also links each research context to the following section reviewing JOM's prior work for each. JOM maintains a continuing focus on TM research about manufacturing technology. At a strategic level, JOM papers studied manufacturing technology strategy (Challis & Samson, 1996) and technology alignment (Cao & Dowlatshahi, 2005; Das & Narasimhan, 2001). A great deal of TM work examined group technology (Jensen et al., 1996), flexible manufacturing system (FMS) technology (Maffei & Meredith, 1995; Turban & Sepehri, 1986), and AMT (Boyer et al., 1997; Boyer & Pagell, 2000; Cagliano & Spina, 2000; Díaz et al., 2003; Small & Yasin, 1997). Research has examined manufacturing task-technology fit (Das & Narasimhan, 2001), technology adoption decisions (Morgan & Daniels, 2001), and implementation aspects (McDermott & Stock, 1999). Using cross-sectional data, JOM empirical research examined drivers and consequences of manufacturing technology use (Heim & Peng, 2010; Kotha & Swamidass, 2000; Swamidass & Kotha, 1998). Manufacturing technology must be nurtured to operate correctly, so research also explored technology maintenance, maintenance outsourcing networks, and maintenance management systems (Gilbert & Finch, 1985; Persona et al., 2007; Stahl & Zimmerer, 1983). Sartal et al. (2020) examined moderating impacts of manufacturers installing technology upon labor productivity for decarbonization initiatives. Studies of service technology explore impacts of technology adoption on service firms. Early research showed successful technology implementation requires clearly defined service processes, which are easily measurable, with technology objectives based on customer needs (Froehle & Roth, 2004; Haynes & Thies, 1991). Technology adoption can influence service process change, which may lead to substantial service innovation (Boone & Ganeshan, 2001; Das & Joshi, 2007). Service technology studies in JOM considered customer contact or organizational learning theoretical lenses to discover impactful service findings (Boone & Ganeshan, 2001; Karwan & Markland, 2006). Early research in service sector technology adoption delivered meaningful implications. Yet, only a few studies explored challenges of technology advancement. Many organizations set an operational strategy of service integration (Xue et al., 2013) or service outsourcing (Modi et al., 2015). During service system changes, firms may face unintended outcomes, such as information breaches (Modi et al., 2015). Addressing these challenges may require studies drawing on different theoretical perspectives, which should be carefully tackled by OM scholars. For example, Ta et al. (2018) used behavioral experiments to study delivery driver attributes for designing crowdsourced delivery services. In-store retailing exhibits its own history of technologies used to enhance retail operations. Yet, while many JOM articles examine retailing issues, few directly relate to in-store technology or TM. Oh et al. (2012) examined multi-channel integration via IT systems in physical retailing, finding such technology enhances innovation and efficiency of retailers, moderated by environmental dynamism. Akturk et al. (2018) examined impacts of ship-to-store technology capabilities in a traditional retailer using an omnichannel approach. JOM has published TM research focused on healthcare technology since the early 1980s. Early papers focused on materials management and aggregate planning technology. Steinberg et al. (1982) documented an MRP system in a private hospital. Connell et al. (1984) studied aggregate planning algorithms interacting with food service systems to enable hospital cost reductions. Today, IT is a crucial factor used to automate and operate healthcare provider systems. Empirical evidence often supports positive associations between healthcare technology and hospital performance, such as care quality or efficiency (Goldstein et al., 2002). TM scholars have studied
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