Industry 4.0, innovation,and sustainable development: A systematic review and a roadmap to sustainable innovation

Despite the recent interest in the Industry 4.0 applications for sustainability, little is known on the processes through which digital transformation and Industry 4.0 technologies enable sustainable innovation in manufacturing. The present study addresses this knowledge gap by developing a strategic roadmap that explains how businesses can leverage Industry 4.0 technologies to introduce sustainability into innovative practices. For this purpose, the study conducts a systematic review of extant literature to identify Industry 4.0 functions for sustainable innovation and applies interpretive structural modeling to devise the promised roadmap. The results offer interesting insights into Industry 4.0 applications for sustainable innovation. The strategic roadmap developed reveals that Industry 4.0 enables sustainable innovation through 11 functions. Industry 4.0 and the underlying digital technologies and principles allow businesses to improve interfunctional collaboration and better integrate with internal and external stakeholders. Industry 4.0 further improves the knowledge base and advanced manufacturing competency and promotes organizational capabilities valuable to sustainable innovation such as green absorptive capacity, sustainable partnership, and sustainable innovation orientation. Through these functions, Industry 4.0 subsequently enhances green process innovation capacity and the ability to develop or reintroduce eco-friendly products economically and competitively. Overall, the roadmap explains the complex precedence relationships among the 11 sustainable innovation functions of Industry 4.0, offering important implications for businesses that seek to leverage Industry 4.0 sustainability implications and manage sustainable development.     

Spatial Analysis and Failure Management in Water Distribution Networks Using Fuzzy Inference System

Water Resources Management - Periodic surface inspections of Water Distribution Networks (WDNs) buried in the soil aren’t possible. Failures, leakage or malfunctioning to these networks...     

Oil prices,growth, and remittance outflows from the Gulf Cooperation Council

How does a decline in oil prices and its impacts on growth affect remittance outflows from the Gulf Cooperation Council (GCC) countries? This paper carries out an empirical analysis of the relationship between oil prices, oil‐ and non‐oil GDP, and remittances outflows from the GCC. The findings of our paper are three folds. First, we find that non‐oil GDP is a key determinant of remittance outflows and that oil GDP is a significant driver of non‐oil GDP in the GCC only in the long term. Second, we document that historically oil prices and remittances tend to broadly move in the same direction but that remittances have been much less volatile than oil prices. An analysis of the past large oil price declines shows that remittance flows to major remittance recipients in Mashreq, Pakistan, and Yemen fell only modestly following large declines in oil prices and recovered quickly in line with oil prices. Finally, we estimate the elasticity of remittance outflows with respect to non‐oil GDP in the GCC using various techniques. Estimates of short‐term elasticity vary between 0.5 and 0.8, while estimates of long‐term elasticity vary between 0.6 and 1.1. We find that construction and government services are two non‐oil GDP components that are strongly associated with remittance outflows.     

Monitoring and Predicting Saltwater Intrusion via Temporal Aquifer Vulnerability Maps and Surrogate Models

This article proposes a methodology to accurately monitor seawater intrusion (SWI) using time-varied GALDIT vulnerability maps. The properly produced samples are then used as input–output patterns for the approximate SWI simulation. As a novelty, the specific area of high susceptibility to SWI is proposed as the dynamic saltwater wedge position to suitably select the monitoring locations (MLs) from a narrowed area. It is observed that varied initial conditions over time periods have more influence than variable pumping rates on salinity at MLs far from the production wells. Support Vector Regression (SVR), Artificial Neural Network (ANN) and Gaussian Process Regression (GPR) models have been substituted for the numerical model of SWI. Input training patterns of the surrogate models are initial salinity concentrations at selected MLs plus transient pumping values via Latin hypercube sampling. The final salinity at MLs constitutes the output patterns. The paper applies this new methodology to a small study area subject to the SWI problem. The generalization ability of surrogate models for predicting new initial conditions-pumping datasets was evaluated using performance criteria considering the ML locations. All surrogates offered good results for predicting SWI at specified MLs. The SVR model had poor performance compared to ANN and GPR models in MLs near the pumping wells, due to their salinity fluctuations over time.

     

European Multi Model Ensemble (EMME): A New Approach for Monthly Forecast of Precipitation

Regarding the ability of data mining algorithms for post-processing the output of climate models, and on the other hand, the successful application of multi-model ensemble approaches in climate forecasts, in this paper, some important data mining algorithms are evaluated for the monthly forecast of precipitation over Iran. For this purpose, four European climate models, from DWD, ECMWF, CMCC and Meteo-France, with six lead times, are used to be post-processed by applying four different algorithms including artificial neural networks, support vector regression, decision tree and random forests. Based on the proposed approach, 72 different models are provided for 12 months, each month with six lead times. The approach is applied for the monthly forecast of precipitation over Iran. According to the results, the neural network and random forest methods performed better than the decision tree and the support vector machine. This advantage preserved for all months of the year. Also, the proposed multi-model approach outperformed any of the individual European models.

     

Cross-licensing agreements in presence of technological improvements

This study investigates the relationship between technologies that firms expect to achieve after cross-licensing (CL) and their incentives for signing CL agreements in a multiproduct-firm setting. Results indicate that if markets are bounded substantial technological improvements that result in removal of firms’ current products from the market may in fact reduce firms’ incentives to negotiate a CL deal. This may also give firms an incentive to agree upon a tacit collusion by which they limit the utilization of CL technologies. However, when markets are unbounded, the prospect of capturing new markets and charging royalty fees can significantly increase firms’ incentives for CL. The rationale behind our modeling assumptions is discussed using example from agriculture biotechnology industry.     

Using the crowd for business model innovation: the case of Digikala

On November 15, 2015, Digikala, one of the largest online stores in the Middle East, launched its first-ever crowdsourcing contest called ‘A glance at tomorrow’. What distinguishes this contest from common crowd-based initiatives is that it was aimed at Business Model Innovation (BMI) rather than product and process innovation. Although using the crowd has proven to be an effective way for firms to boost their product and process innovation, its use for BMI is challenging. Based on real large-scale data from the Digikala’s crowdsourcing contest, this research focuses on the application of crowd-powered solutions in BMI, which has rarely been investigated previously. Our exploratory case study indicates that the crowd could contribute to the BMI process. Our findings point to a new form of ‘division of innovation labor’ in BMI. Contribution of the crowd in BMI is more likely to be relevant to Value Proposition and Value Delivery, while it might be less relevant to Value Capture and Value Creation. The results also support the notion that crowd-contributor characteristics affect the quality of proposals for BMI. We argue that this line of research could help companies design and implement customized crowd-based initiatives to better support their BMI process.     

A Novel Idea for Groundwater Resource Management during Megadrought Events

Water Resources Management - Due to the effects of global climate change on duration, frequency and number of drought events, the occurrence of prolonged droughts, referred to as...     

A New Linear Programming Method for Weights Generation and Group Decision Making in the Analytic Hierarchy Process

This paper proposes a new linear programming method entitled by LP-GW-AHP for weights generation in analytic hierarchy process (AHP) which employs concepts from data envelopment analysis. We propose four specially constructed linear programming (LP) models which are used to derive weight vector from a pair-wise comparison matrix or a group of them. We can use both interval and relative importance weights for each decision maker in LP-GW-AHP. In this method, solving only one LP model is enough for local weights derivation from pair-wise comparison matrices. Five numerical examples are examined to illustrate the potential applications of the LP-GW-AHP method. We show that not only derived weights of the new method have slight differences than Saaty’s eigenvector weights but sometimes they are better than eigenvector method weights in the fitting performance index as well. LP-GW-AHP is compared with a method which has been recently proposed for the weights derivation in the group AHP and it becomes obvious that LP-GW-AHP provides better weights. The simple additive weighting method is utilized to aggregate local weights without the need to normalize them.     

Evaluating Willingness-to-Pay for Bison Attributes: An Experimental Auction Approach

Domestic bison herds in Canada and the United States have grown rapidly over the past decade. For this growth to be sustainable, viable markets for bison meat products are necessary. Bison products are available at the retail level to only a limited extent in some localized markets. Very little is known about consumer preferences for bison in Canada. A consumer research study was conducted across five Canadian locations. An experimental auction was used to evaluate willingness‐to‐pay (WTP) for bison versus beef, plus the marginal WTP for bison with additional health‐related attributes. Bison products verified to be lower in fat than beef, and bison verified to have been produced without the use of growth hormones were evaluated. Results suggest that there was no significant WTP for bison over beef, either with or without the additional quality assurances. Delivering a positive eating experience to consumers was more important than the health‐related attributes per se. Distinct market segments with significantly different WTP for bison are identified. Some regional differences are also apparent. The industry cannot rely solely on the touted health benefits of bison to deliver a competitive advantage over beef. While some consumers may be willing to pay more for these health‐related attributes, consumers in general are unlikely to compromise eating experience. Au Canada et aux États‐Unis, les troupeaux de bisons domestiques ont crû rapidement au cours de la dernière décennie. Pour que cette croissance soit durable, il faut développer des marchés viables pour le bison. Le bison est vendu au détail dans quelques marchés locaux seulement. Au Canada, les préférences des consommateurs pour le bison sont peu connues. Une étude à cet effet a été réalisée dans cinq villes canadiennes. La volonté de payer (VDP) des consommateurs pour du bison plutôt que pour du b?uf de même que la VDP marginale des consommateurs pour du bison ayant des propriétés supplémentaires pour la santé ont étéévaluées à l'aide d'enchères expérimentales. Des produits du bison ayant une teneur en gras inférieure à celle du b?uf et provenant d'élevages sans hormones de croissance ont étéévalués. Les résultats ont montré qu'il n'existait pas de VDP significative pour du bison plutôt que pour du b?uf, et ce, avec ou sans assurance de qualité supplémentaire. L'expérience alimentaire s'est révélée plus importante que les propriétés pour la santé en soi. Nous avons identifié des segments de marché distincts où la VDP pour du bison était significativement différente. Certaines différences régionales étaient aussi apparentes. L'industrie ne peut pas se fier qu'aux avantages vantés de la viande de bison pour la santé pour offrir un avantage concurrentiel par rapport au b?uf. Bien que certains consommateurs soient prêts à payer davantage pour des propriétés favorables pour la santé, il est peu probable que les consommateurs en général compromettent une nouvelle expérience alimentaire.