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This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

Entering and exiting the Pandemic Recession, the author study the high-frequency real-activity signals provided by a leading nowcast, the ADS Index of Business Conditions produced and released in real time by the Federal Reserve Bank of Philadelphia. The author tracks the evolution of real-time vintage beliefs and compares them to a later-vintage chronology. Real-time ADS plunges and then swings as its underlying economic indicators swing, but the ADS paths quickly converge to indicate a return to brisk positive growth by mid-May. The author shows, moreover, that the daily real-activity path was highly correlated with the daily COVID-19 cases. Finally, the author provides a comparative assessment of the real-time ADS signals provided when exiting the Great Recession.

Purpose – This chapter provides details of research that attempts to relate traffic operational conditions on uninterrupted flow facilities (e.g., freeways and expressways) with real-time crash likelihood. Unlike incident detection, the purpose of this line of work is to proactively assess crash likelihood and potentially reduce the likelihood through proactive traffic management techniques, including variable speed limit and ramp metering among others.

Methodology – The chapter distinguishes between the traditional aggregate crash frequency-based approach to safety evaluation and the approach needed for real-time crash risk estimation. Key references from the literature are summarised in terms of the reported effect of different traffic characteristics that can be derived in near real-time, including average speed, temporal variation in speed, volume and lane-occupancy, on crash occurrence.

Findings – Traffic and weather parameters are among the real-time crash-contributing factors. Among the most significant traffic parameters is speed particularly in the form of coefficient of variation of speed.

Research implications – In the traffic safety field, traditional data sources are infrastructure-based traffic detection systems. In the future, if automatic traffic detection systems could provide reliable data at the vehicle level, new variables such as headway could be introduced. Transferability of real-time crash prediction models is also of interest. Also, the potential effects of different management strategies to reduce real-time crash risk could be evaluated in a simulation environment.

Practical implications – This line of research has been at the forefront of bringing data mining and other machine-learning techniques into the traffic management arena. We expect these analysis techniques to play a more important role in real-time traffic management, not just for safety evaluation but also for congestion pricing and alternate routing.

This study develops and validates a theoretical model of real-time mobile connectivity, examining how employees' perceptions of their relationship with supervisors influence their emotional experiences. Through quasi-experiments, the authors investigate the behavioral patterns and emotional responses associated with real-time mobile connectivity in organizations, with a focus on messaging apps that indicate message read status. Specifically, they explore how supervisors' attentiveness or inattentiveness in mobile connectivity impacts emotional ambivalence (anxiety and pride) among subordinates. Additionally, they examine the downstream effects of this emotional ambivalence on employees' workplace thriving and job performance across various dimensions.

To address the paradox of real-time mobile connectivity, a quasi-experimental design involving 320 team members from 46 teams was implemented. Multi-level structural equation modeling was employed to analyze within-person variance and evaluate the proposed hypotheses.

The findings indicate that employees who do not receive timely indications from their supervisors are more likely to experience elevated levels of anxiety, while those who receive prompt indications experience a sense of pride. Moreover, the indirect effects of the real-time mobile connectivity paradox on employee performance, mediated by anxiety (negatively) and pride (positively), are fully explained through workplace thriving.

This study provides insights into the emotional ambivalence experienced in the workplace due to real-time mobile connectivity, highlighting its implications for organizational competitiveness. Integrating resource conservation theory and cognitive appraisal theory of emotion, the study explores the mediating role of workplace thriving and the impact on employee performance through pride and anxiety. Generalizability requires considering organizational settings and cultural contexts while acknowledging limitations such as a focus on messaging apps and specific samples. Future research should explore these dynamics in diverse contexts and identify additional factors influencing the relationship between real-time mobile connectivity and employee outcomes.

This study provides valuable insights for managers regarding the significance of message indications, as their attentiveness can elicit emotional reactions from employees that subsequently impact workplace thriving and job performance.

This study pioneers the exploration of the paradox of real-time mobile connectivity in the workplace, uncovering the discrete emotions experienced by employees. Furthermore, it elucidates the subsequent opposing effects on workplace thriving and job performance, contributing to the existing literature and knowledge in this area.

This study aims to explore how brands use brand personification techniques in real-time marketing on social media, particularly Twitter, and examine how these techniques impact consumer engagement, moderated by brand-event congruence levels.

Data included 464 tweets posted by 95 brands around three large events in 2019. The types of brand personification techniques and the level of brand-event congruence applied by the tweets were content-analyzed, and regression analyses were conducted to examine their linkages to consumer engagement metrics.

Results confirmed the use of diverse personification techniques in brands’ real-time marketing tweets as in the previous literature. The study also revealed a new personification technique, tacit expression, not reported in previous literature. The study also showed that the overall effectiveness of multimedia-based (vs caption-based) personification techniques in increasing consumer engagement on social media was greater, but their relative effectiveness varied depending on whether or not the event was functionally congruent with the brand.

The findings offer valuable suggestions to brand managers regarding prioritizing brand personification techniques and aligning brands’ social media marketing with real-time events to maximize the effectiveness of real-time marketing in boosting consumer engagement.

This research offers insights into the dynamic effects of different brand personification techniques in the new context of real-time marketing, extending the scope of literature on brand personification and anthropomorphism. The revelation of a new type of brand personification not captured in the extant literature is also a significant contribution.

The study objective was to understand what components of organizational culture and capability combined with analytic skillsets are needed to allow organizations to exploit real-time analytic technologies to create supply chain performance improvements.

The authors relied on information processing theory to support a hypothesized model, which is empirically tested using an ordinary least squares equation model, and survey data from a sample of 208 supply chain executives across multiple industries.

The authors found strong support for the concept that real-time analytics will require specialized analytical skills for the managers who use them in their daily work, as well as an analytics-focused organizational culture that promotes data visibility and fact-based decision-making.

Based on the study model, the authors found that a cultural bias to embrace analytics and a strong background in statistical fluency can produce decision-makers who can make sense of a sea of data, and derive significant supply chain performance improvements.

The research was initiated through five workshops and presentations with supply chain executives leading real-time analytics initiatives within their organizations, which were then mapped onto survey items and tested. The authors complement our findings with direct observations from managers that lend unique insights into the field.

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.

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.

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.

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.

Visibility is the need of the hour for each organization involved in the supply chain, and scholars have made few previous efforts to understand patterns driving visibility in transportation platforms. However, many companies have not been able to achieve sufficient levels of practical implementation across the supply chain. Therefore, this study focuses on exploring, why the real-time visibility transportation platforms fail to operationalize.

This study utilizes action research as a methodology for pragmatism to understand supply chain professionals' viewpoint regarding the operationalization of real-time visibility. The research addresses a complex transportation network of a fast-moving consumer goods company. Wherein, both a greater need for visibility and improvements are also more challenging.

Tensions amongst complementors, the platform owner, and the Control Tower of a focal company explain the different impacts of freight forwarders and own fleet carriers on shipment compliance. Integrating subcontractors is a cost-intensive practice for complementors that increases asymmetry and reduces co-created value. The willingness of freight forwarders to exert control contributes to tension competition versus collaboration.

The model identifies the dynamics that explain how managers can navigate the tension over time by controlling contradictory loops driving shipment compliance. Findings can help managers develop plans, conduct pilots, and collaborate to unlock value from real-time visibility. The research findings can be informative for the European Union bodies and help work out a policy that reduces the asymmetry of benefits and contribute to the more sustainable development of digital industrial platforms.

The contribution lies in (1) providing a study of the factors affecting achieving real-time visibility, (2) distinguishing complementors (3) identifying tensions amongst complementors and platform owner as critical for successful platform deployment, (4) conceptualizing a pattern of behavior emerging amongst the platform partners and (5) outlining avenues for future research.

The purpose of this paper is to investigate the critical time window for pro-active construction accident prevention and response. Large to small organisations throughout the entire construction supply chain continue to be challenged to adequately prevent accidents. Construction worker injuries and fatalities represent significant waste of resources. Although the five C’s (culture, competency, communication, controls and contractors) have been focusing on compliance, good practices and best-in-class strategies, even industry leaders have only marginal improvements in recorded safety statistics for many years.

Right-time vs real-time construction safety and health identifies three major focus areas to aid in the development of a strategic, as opposed to tactical, response. Occupational safety and health by design, real-time safety and health monitoring and alerts and education, training and feedback leveraging state-of-the-art technology provide meaningful predictive, quantitative and qualitative measures to identify, correlate and eliminate hazards before workers get injured or incidents cause collateral damage.

The current state and development of existing innovative initiatives in the occupational construction safety and health domain are identified. A framework for right-time vs real-time construction safety and health presents the specific focus on automated safety and health data gathering, analysis and reporting to achieve better safety performance. The developed roadmap for right-time vs real-time safety and health is finally tested in selected application scenarios of high concern in the construction industry.

A strategic roadmap to eliminate hazards and accidents through right-time vs real-time automation is presented that has practical as well as social implications on conducting a rigorous safety culture and climate in a construction business and its entire supply chain.

Recently, many countries have been pushing for a higher share of renewable energy sources, especially wind, in their generation mix. However, the intermittent and uncertain nature of wind power imposes a limit on the extent it can replace the conventional generation resources. In a high wind penetration scenario, the Battery Energy Storage System (BESS) offers a solution to the grid operation problems. The purpose of this paper is to evaluate the merits of price‐based operation of BESS in a real‐time market with high wind penetration using frequency‐linked pricing.

The authors propose a real‐time market in which real‐time prices are based on the grid frequency. A model for real‐time price‐based operation of a conventional generator and a BESS is presented. Simulations for different wind penetration scenarios are carried out on an isolated area test system. Wind speed sequence is generated using composite wind speed model. A simplified model of wind speed to power conversion is adopted to observe the impact of increase in wind power generation on the grid frequency and the real‐time prices.

The result of simulations show that BESS not only helps in dealing with uncertainty in wind power forecasts, but also reduces the fluctuations in frequency due to wind power's intermittency. Price‐based operation of BESS results in higher operating revenues by discharging it at peak prices and reduces operating costs by charging it at minimum prices.

The study helps in achieving the societal goal of replacing fossil fuel generation by environment friendly generation and reducing green house gas emissions.

The novelty of this paper lies in the use of frequency‐linked pricing in real‐time market and proposing a control algorithm for operating BESS using these price signals.