Industrial Management & Data Systems

Publisher:: Emerald Group Publishing Limited
Publication date:: 2021-02-01

ISBN:: 0263-5577

Issue Number

Latest documents

Guest editorial: The role of Industry 4.0 in enabling circular economy
Smart home devices and B2C e-commerce: a way to reduce failed deliveries
Purpose: Failed deliveries (i.e. deliveries not accomplished due to the absence of customers) represent a critical issue in B2C (Business-to-consumer) e-commerce last-mile deliveries, implying high costs for e-commerce players and negatively affecting customer satisfaction. A promising option to reduce them would be scheduling deliveries based on the probability to find customers at home. This work proposes a solution based on presence data (gathered through Internet of Things [IoT] devices) to organise the delivery tours, which aims to both minimise the travelled distance and maximise the probability to find customers at home. Design/methodology/approach: The adopted methodology is a multi-method approach, based on interviews with practitioners. A model is developed and applied to Milan (Italy) to compare the performance of the proposed innovative solution with traditional home deliveries (both in terms of cost and delivery success rate). Findings: The proposed solution implies a significant reduction of missed deliveries if compared to the traditional operating mode. Accordingly, even if allocating the customers to time windows based on their availability profiles (APs) entails an increase in the total travel time, the average delivery cost per parcel decreases. Originality/value: On the academic side, this work proposes and evaluates an innovative last-mile delivery (LMD) solution that exploits new AI (Artificial Intelligence)-based technological trends. On the managerial side, it proposes an efficient and effective novel option for scheduling last-mile deliveries based on the use of smart home devices, which has a significant impact in reducing costs and increasing the service level.
Innovating in data-driven production environments: simulation analysis of Net-CONWIP priority rule
Purpose: Motivated by recent research indicating that the operational performance of an enterprise can be enhanced by building a supporting data-driven environment in which to operate, this paper presents a simulation framework that enables an examination of the effects of applying smart manufacturing principles to conventional production systems, intending to transition to digital platforms. Design/methodology/approach: To investigate the extent to which conventional production systems can be transformed into novel data-driven environments, the well-known constant work-in-process (CONWIP) production systems and considered production sequencing assignments in flowshops were studied. As a result, a novel data-driven priority heuristic, Net-CONWIP was designed and studied, based on the ability to collect real-time information about customer demand and work-in-process inventory, which was applied as part of a distributed and decentralised production sequencing analysis. Application of heuristics like the Net-CONWIP is only possible through the ability to collect and use real-time data offered by a data-driven system. A four-stage application framework to assist practitioners in applying the proposed model was created. Findings: To assess the robustness of the Net-CONWIP heuristic under the simultaneous effects of different levels of demand, its different levels of variability and the presence of bottlenecks, the performance of Net-CONWIP with conventional CONWIP systems that use first come, first served priority rule was compared. The results show that the Net-CONWIP priority rule significantly reduced customer wait time in all cases relative to FCFS. Originality/value: Previous research suggests there is considerable value in creating data-driven environments. This study provides a simulation framework that guides the construction of a digital transformation environment. The suggested framework facilitates the inclusion and analysis of relevant smart manufacturing principles in production systems and enables the design and testing of new heuristics that employ real-time data to improve operational performance. An approach that can guide the structuring of data-driven environments in production systems is currently lacking. This paper bridges this gap by proposing a framework to facilitate the design of digital transformation activities, explore their impact on production systems and improve their operational performance.
Modeling customer satisfaction and revisit intention from online restaurant reviews: an attribute-level analysis
Purpose: The purpose of this paper is to detect predefined service attributes and their sentiments from online restaurant reviews, and then to measure the effects of customer sentiments toward service attributes on customer satisfaction (CS) and revisit intention (RVI) simultaneously. Design/methodology/approach: This study proposed a supervised framework to model CS and RVI simultaneously from restaurant reviews. Specifically, the authors detected the predefined service dimensions from online reviews based on random forest. Then, the sentiment polarities of the reviews toward each predefined dimension were identified using light-gradient boosting machine (LightGBM). Finally, the effects of attribute-specific sentiments on CS and RVI were evaluated by a bagged neural network-based model. The proposed framework was evaluated by 305,000 restaurant comments collected from DianPing.com, a Yelp-like website in China. Findings: The authors obtained a hierarchal importance order of the investigated service themes (i.e. location, service, environment, price and food). The authors found that food played the most important role in affecting both CS and RVI. The most salient attribute with respect to each service theme was also identified. Originality/value: Unlike prior work relying on the data collected from surveys, this study is among the first to model the relationship among service attributes, CS and RVI simultaneously from real-world data. The authors established a hierarchal structure of eighteen attributes within five service themes and estimated their effects on both CS and RVI, which will broaden our understanding of customer perception and behavioral intention during service consumption.
Understanding investor co-investment in a syndicate on equity crowdfunding platforms
Purpose: Considering the unique characteristics of equity crowdfunding platforms including the removal of stringent structural barriers (e.g. lack of co-location), high visibility and traceability of investor characteristics, large pool of available investors and simplified transaction process, the authors aim to examine how the two most prevalent mechanisms (i.e. homophily and repeated ties) unfold in this context by incorporating the contextual characteristics. The authors theorize an inverted U-shaped relationship between leader-backer similarity and the likelihood of co-investment in a syndicate on equity crowdfunding platforms. In addition, a leader–backer dyad is more likely to form new syndicates if the students have more prior co-investment ties. Design/methodology/approach: The empirical study is based on data from the AngelList syndicate platform and a linear probability model (LPM) with fixed effects is adopted to estimate the syndicate formation. Findings: The authors find that the similarity between a leader and a backer has an inverted U-shaped relationship with the leader and backer's likelihood of co-investment in a syndicate, which is different from the dominant homophily-based tie formation in venture capital (VC) syndicates and other digital platform contexts. Although equity crowdfunding platforms encourage the possibility of exploring new partners, investors are more likely to co-invest with others who have stronger prior ties. Originality/value: This research theoretically contributes to the scant literature of equity crowdfunding syndicates by contextualizing two most prevalent mechanisms (i.e. homophily and repeated ties) driving tie formation in VC syndicates and digital platforms.
The viewer value co-creation process on sports live streaming platforms
Purpose: The Sports Live Streaming Platforms (SLSPs) have taken centre stage in broadcasting sporting events. This study adopts the value creation sphere (VCS) model and the service dominant logic (SDL) to unpack the value co-creation process on SLSPs. Design/methodology/approach: A case study with one of the most representative SLSPs in China, involving the netnographic approach and in-depth interviews, was conducted. Findings: This study redefines the value co-creation spheres in the context of SLSPs and identifies four actors who contribute to viewers' value perceptions. The findings show that viewers' values can be co-created individually and collectively with other actors in both the customer sphere and the joint sphere. Originality/value: This study extends the theoretical boundary of value co-creation into the context of SLSPs. The study findings help SLSPs managers and decision makers understand the value co-creation process to gain competitive advantages and enhance the sustainability of their services.
Does online–offline channel integration matter for supply chain resilience? The moderating role of environmental uncertainty
Purpose: Drawing on dynamic capability theory, this study investigates how online–offline channel integration (OOCI) affects a firm's supply chain resilience and how such an effect is moderated by market turbulence and regulatory uncertainty. Design/methodology/approach: A sample of 273 Chinese firms that conduct online and offline business and hierarchical regression analysis were used to examine the research model. Findings: The results suggest that the effect of OOCI on supply chain resilience differs in terms of its dimensions (i.e. information integration, transaction integration and service integration). While information integration and service integration were positively associated with supply chain resilience, transaction integration had a non-significant relationship with supply chain resilience. Moreover, market turbulence negatively moderated the effect of transaction integration and positively moderated the effect of service integration. Regulatory uncertainty positively moderated the effect of transaction integration and negatively moderated the effect of service integration. Implications and suggestions for future research are discussed. Originality/value: This study examines the effect of OOCI on supply chain resilience. It further explores the influence of market turbulence and regulatory uncertainty on the relationship between OOCI and supply chain resilience.
Dynamic perceived quality analysis using social media data at macro- and micro-levels
Purpose: This paper aims to propose a method for dynamic product perceived quality analysis using social media data and to achieve a macro–micro combination analysis. The method enables the prioritization of perceived quality attributes and provides perception causes. Design/methodology/approach: To rationalize the macro–micro combination, ANOVA and multiple linear regression were used to identify the main factors affecting perceived quality which served as the combination basis; by using the combination basis for consumer segmentation, macro-knowledge (i.e. attribute importance and quality category of the attribute) is achieved by term frequency-inverse document frequency (TF-IDF)-based attribute importance calculation and KANO-based attribute classification, which is combined with micro-quality diagnostic information (i.e. perceived quality, perception causes and quality parameters). Further, dynamic perception Importance-Performance Analysis (IPA) is built to present the attribute priority and perception causes. Findings: The framework was validated by the new energy vehicle (NEV) data of Autohome. The results show that price and purchase purpose are the most influential factors of perceived quality and that dynamic perception IPA can effectively prioritize attributes and mine perception causes. Originality/value: This is one of the first studies to analyze dynamic perceived quality using social media data, which contributes to the research on perceived quality. The paper also contributes by achieving a combined macro–micro analysis of perceived quality. The method rationalizes the macro–micro combination by identifying the factors influencing perceived quality, which provides ideas for other studies using social media data.
An exploratory study of organisational and industry drivers for the implementation of emerging technologies in logistics
Purpose: Emerging technologies have the capacity to transform industries offering substantial benefits to users. Given the increasing demand for advanced logistics services, third-party logistic service providers (LSPs) face greater pressure to deploy and realise these technologies, especially given the demands and operational challenges created during the COVID-19 crisis. Drawing upon the diffusion of innovation (DOI) theory and technology–organisation–environment (TOE) framework, this paper goes beyond just identifying drivers and barriers to technology adoption to understanding how LSPs and industry experts perceive these drivers and barriers and simultaneously confront and undertake actions to implement them. Design/methodology/approach: An exploratory study was conducted in three phases: (1) in-depth interviews with twelve stakeholders in the Australian logistics industry; (2) five in-depth interviews conducted with stakeholders during the COVID-19 crisis and (3) a focus group discussion session. All interviews were analysed using content analysis and revealed several drivers for the deployment of emerging technologies, including internal organisational factors that drive supply chain (SC) network optimisation. Findings: The analysis of the three phases identified several drivers for the deployment of emerging technologies in logistics, including internal organisational factors that drive SC network optimisation. Also identified were external drivers including the impact of the COVID-19 crisis, along with barriers and specific actions that were considered and implemented by LSPs for sustainable operations, particularly in a post-COVID-19 environment. Originality/value: This study explores organisational and industry drivers for the implementation of emerging technologies. Explicitly, it extends the extant research by highlighting organisational and industry drivers and enablers that influence adoption and deployment of emerging technologies. Second, it advances the existing perspectives on LSPs in the Australian context on the development and implementation of technology strategies. The paper offers insights around implementation of technologies, directly obtained from industrial application for managers and practitioners.
Industrialisation, ecologicalisation and digitalisation (IED): building a theoretical framework for sustainable development
Purpose: In the past two decades, manufacturing has witnessed significant transformations alongside ecological challenges. Meanwhile, industrial 4.0 digital technologies have accelerated industrialisation with potentials of innovation in the context of circular economy. However, current concepts and models are fragmented and impractical. This paper aims to develop a holistic view integrating the three bodies of knowledge – industrialisation, ecologicalisation and digitalisation (IED) – in order to achieve sustainable development. Design/methodology/approach: Critical literature review is conducted across three bodies of knowledge. Key themes are summarised with the identification of research gaps. A theoretical framework is synthesised and developed aiming to achieve synergy from IED with the modules, integration architecture, mechanism and dynamic paths. Findings: First, the authors review and develop three conceptual models of ecologicalised industrialisation (IE3), industrial system digitalisation (D1) and digital technology industrialisation (D2) separately. Second, the authors propose a theoretical framework seeking to synthesise the above three conceptual models together to form the IED. Third, the authors design a process orientated abductive approach to improve and validate the IED framework. Originality/value: This study contributes to the limited literature addressing the linkage of IED by integration different perspectives to develop theory in a novel way. Practically, it provides important tools for organisations to consider resource cascading in combination with digitalisation during the industrial system design.