RFID-enabled item-level product information revelation

We consider a homogeneous product market and the incentive for oligopolists to share item-level product information with their customers. Enabled by Radio Frequency Identification technology, each firm has the option to record and reveal item-level information of a proportion of its products. We consider a two-stage game where each firm first decides its production plan and then determines its level of information revelation. With a constant clearance discount rate, we derive pure strategy equilibria that are subgame perfect and demonstrate that complete information sharing is the unique Nash equilibrium for the game when the common demand is volatile and that no information revelation is the unique Nash equilibrium when demand is not volatile. Furthermore, we show that the Nash equilibrium is the same with a decreasing clearance discount rate and that neither complete information revelation nor zero information revelation is consistent with an equilibrium with an increasing discount rate. Results are similar in a duopoly non-homogeneous product market scenario.     

Vulnerabilities in Chen and Deng's RFID mutual authentication and privacy protection protocol

As incorporation of RFID (Radio Frequency IDentification) tags in a wide variety of applications increase, there is a need to ensure the security and privacy of the entity to which these tags are attached. Not surprisingly, this is a very active area as attested by the large number of related published research literature. Recently, the journal engineering applications of artificial intelligence published a paper by Chen and Deng (2009) where the authors propose a mutual authentication protocol for RFID. This protocol has fundamental flaws that can be readily taken advantage by a resourceful adversary. We identify and discuss these vulnerabilities and point out the characteristics of this protocol that exposes it to these vulnerabilities.     

Exploratory analysis of factors influencing performance dynamics oftelecommuters and traditional office workers

Advances in information technology are enabling the formation of new work arrangements, where employees may perform work activities at any location, at any time. This includes remote locations such as an employee's home or a satellite office. When employees work remotely, there are fewer opportunities for face-to-face (FTF) communication, and more communication occurs in non-FTF modes. Communication is a crucial component of the work process and can affect the performance of work activities. Clearly, the resources necessary to provide an effective work environment are different for traditional and remote workers. It is thus critical to identify and study the dynamics of this environment to foster effective job performance. The authors are particularly interested in the use of communication to coordinate work activities and the resulting effect on performance. We investigate the difference in use of formal, informal, and electronic coordination techniques in the remote and traditional work environments. We also investigate the influence of job characteristics and information technology (IT) factors on job performance in both work environments. The study was conducted through a survey of a large number of telecommuters and a control group of nontelecommuters in eight firms in Atlanta (USA). We use inductive learning to identify patterns of behavior present in the data. Results from the study indicate communication needs in this work environment are much more complex than previously recognized. The research indicates that the method of use of communication channels and the communication partner must be considered, in addition to the work environment of the individual to provide an atmosphere conducive to good performance. We also found that job characteristics and IT factors had differing effects on the groups which should be explored further     

Real-Time business data acquisition: How frequent is frequent enough?

Effective data acquisition for business process monitoring has become a critical element in today’s business world. While the need for monitoring is generally agreed upon by both re- searchers and practitioners alike, the means and mechanisms are often vague. This is especially salient with the fast growing availability of various technologies to monitor in real-time through recent advances such as the Internet of Things (IoT) with specific emphasis on Radio-Frequency IDentification (RFID) and associated sensor networks. This study is motivated by the lack of published literature in data acquisition and analytics that specifically addresses sufficient real-time data acquisition for effective managerial monitoring. As a step in addressing this void, we review and extend existing literature in this general area by studying various requirements and information sources that relate to effective management monitoring. We then design an exploratory study to evaluate current managerial monitoring needs and the importance of automated data collection technologies. Results from this study show that the most important latent factor that influences an organization’s information need is its dynamic competitiveness, and consequently, companies with a dynamic supply chain would need a faster transaction and operations data system. The second important latent factor is the behavioral performance, which renders it essential to have a human-centric data system. This study provides evidence for the significance in adopting technologies such as RFID and other IoT systems for real-time monitoring in highly dynamic organizations and offers guidelines for analytical technology adoption for various industries.     

Information-Based Dynamic Manufacturing System Scheduling

Information about the state of the system is of paramount importance in determining the dynamics underlying manufacturing systems. In this paper, we present an adaptive scheduling policy for dynamic manufacturing system scheduling using information obtained from snapshots of the system at various points in time. Specifically, the framework presented allows for information-based dynamic scheduling where information collected about the system is used to (1) adjust appropriate parameters in the system and (2) search or optimize using genetic algorithms. The main feature of this policy is that it tailors the dispatching rule to be used at a given point in time to the prevailing state of the system. Experimental studies indicate the superiority of the suggested approach over the alternative approach involving the repeated application of a single dispatching rule for randomly generated test problems as well as a real system. In pa ticular, its relative performance improves further when there are frequent disruptions and when disruptions are caused by the introduction of tight due date jobs and machine breakdown—two of the most common sources of disruption in most manufacturing systems. From an operational perspective, the most important characteristics of the pattern-directed scheduling approach are its ability to incorporate the idiosyncratic characteristics of the given system into the dispatching rule selection process and its ability to refine itself incrementally on a continual basis by taking new system parameters into account.     

Security of lightweight mutual authentication protocols

Sensors and IoT (Internet of Things), which include RFID (Radio-Frequency IDentification) tags, have witnessed widespread adoption across a wide variety of application domains over the last two decades. These sensors and IoT devices are often a part of distributed sensor networks. As with any distributed processing scenario, there is a need to ensure that these devices provide required security and privacy to the tagged object as well as its bearer. Cryptography has been used to address the security and privacy aspects of RFID tags. Unlike a majority of other IoT devices, the commonly used passive RFID tags are extremely resource-constrained and therefore can accommodate only lightweight operations. Security and privacy concerns still need to be addressed as they remain significant regardless of implementation details. We evaluate RFID-based lightweight mutual authentication protocols that have been recently proposed and identify vulnerabilities.

     

Recent advances and opportunities in sustainable food supply chain: a model-oriented review

Faced with the challenges associated with sustainably feeding the world’s growing population, the food industry is increasingly relying on operations research (OR) techniques to achieve economic, environmental and social sustainability. It is therefore important to understand the context-specific model-oriented applications of OR techniques in the sustainable food supply chain (SFSC) domain. While existing food supply chain reviews provide an excellent basis for this process, the explicit consideration of sustainability from a model-oriented perspective along with a structured outline of relevant SFSC research techniques are missing in extant literature. We attempt to fill this gap by reviewing 83 related scientific journal publications that utilise mathematical modelling techniques to address issues in SFSC. To this end, we first identify the salient dimensions that include economic, environmental and social issues in SFSC. We then review the models and methods that use these dimensions to solve issues that arise in SFSC. We identify some of the main challenges in analytical modelling of SFSC as well as future research directions.     

Challenges associated with RFID tag implementations in supply chains

Radio-Frequency Identification (RFID) tags are gaining widespread popularity throughout the supply chain from raw material acquisition, manufacturing, transportation, warehousing, retailing to the ultimate consumers. A majority of extant literature in this area explore the beneficial aspects of RFID tags such as their batch readability, resistance to harsh environmental conditions, information storage and processing capability, among others. Given the recent explosion of interest in RFID tag incorporation in supply chains, literature in the area has not yet comprehensively identified nor addressed associated challenges and impediments to successful implementations. We purport to fill this gap and to raise awareness by identifying and discussing critical issues such as ownership transfer, privacy/security, computing bottleneck, read error, and cost-benefit issues such as opportunity cost, risk of obsolescence, information sharing, and inter-operability standards.     

Inductive Learning Methods for Knowledge-Based Decision Support: A Comparative Analysis

This paper describes the inductive learning methods for generating decision rules in decision support systems. Three similarity-based learning systems are studied based on: (1) the AQ-Star method, (2) the Tree-Induction method, and (3) the Probabilistic Learning method. Loan evaluation examples and empirical data are used as a basis for comparing these inductive learning methods on their algorithmic characteristics and decision support performance.     

Machine learning for dynamic multi-product supply chain formation

Recent trend in eCommerce applications toward effectively reducing supply chain costs—including spatial, temporal, and monetary resources—has spurred interest among researchers as well as practitioners to efficiently utilize supply chains. One of the least studied of these views is adaptive or dynamic configuration of supply chains. This problem is relatively new since faster communications over the Internet or by any other means and the willingness to utilize it for effective management of supply chains did not exist a few decades ago. The proposed framework addresses the problem of supply chain configuration. We incorporate machine-learning techniques to develop a dynamically configurable supply chain framework, and evaluate its effectiveness with respect to comparable static supply chains. Specifically, we consider the case where several parts go into the production of a product. A single supplier or a combination of suppliers could supply these parts. The proposed framework automatically forms the supply chain dynamically as per the dictates of incoming orders and the constraints from suppliers upstream.