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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.

The heating, ventilation and air conditioning systems are responsible for a significant proportion of the energy consumption of the built environment, on which the occupant's pursuit of thermal comfort has a substantial impact. Regarding this concern, current software can assess and visualize the conditions. However; integration of existing technologies and real-time information could enhance the potential of the solution proposals. Therefore, the purpose of this research is to explore new possibilities of how to upgrade building information modeling (BIM) technology to be interactive; by using existing BIM data during the occupation phase. Moreover, the research discusses the potential of enhancing energy efficiency and comfort maximization together by using the existing BIM database and real-time information concomitantly.

The platform is developed by designing and testing via prototyping method thanks to Internet of things technologies. The algorithm of the prototype uses real-time indoor thermal information and real-time weather information together with user's body temperature. Moreover, the platform processes the thermal values with specific material information from the existing BIM file. The final prototype is tested by a case study model.

The outcome of the study, “Symbiotic Data Platform” is an occupant-operated tool, that has a hardware, software and unique Revit-Dynamo definition that implies to all BIM files.

The paper explains the development of “Symbiotic Data Platform”, which presents an interactive phase for BIM, as creating a possibility to use the existing BIM database and real-time values during the occupation phase, which is operated by the occupants of the building; without requiring any prior knowledge upon any of the BIM software or IoT technology.

Creating a real-time data integration when developing an internet-of-things (IoT)-based warehouse is still faced with challenges. It involves a diverse knowledge of novel technology and skills. This study aims to identify the critical components of the real-time data integration processes in IoT-based warehousing. Then, design and apply a data integration framework, adopting the IoT concept to enable real-time data transfer and sharing.

The study used a pilot experiment to verify the data integration system configuration. Radio-frequency identification (RFID) technology was selected to support the integration process in this study, as it is one of the most recognized products of IoT.

The experimentations’ results proved that data integration plays a significant role in structuring a combination of assorted data on the IoT-based warehouse from various locations in a real-time manner. This study concluded that real-time data integration processes in IoT-based warehousing could be generated into three significant components: configuration, databasing and transmission.

While the framework in this research was carried out in one of the developing counties, this study’s findings could be used as a foundation for future research in a smart warehouse, IoT and related topics. The study provides guidelines for practitioners to design a low-cost IoT-based smart warehouse system to obtain more accurate and timely data to support the quick decision-making process.

The research at hand provides the groundwork for researchers to explore the proposed theoretical framework and develop it further to increase inventory management efficiency of warehouse operations. Besides, this study offers an economical alternate for an organization to implement the integration software reasonably.

While several warehouses are now technologically equipped and smart, the implementation of real-time analytics in warehouse operations is scarcely reported in the literature. This study aims to develop a practical system for real-time analytics of process monitoring in an internet-of-things (IoT)-enabled smart warehouse environment.

A modified system development research process was used to carry out this research. A prototype system was developed that mimicked a case company’s actual warehouse operations in Indonesia’s manufacturing companies. The proposed system relied heavily on the utilization of IoT technologies, wireless internet connection and web services to keep track of the product movement to provide real-time access to critical warehousing activities, helping make better, faster and more informed decisions.

The proposed system in the presented case company increased real-time warehousing processes visibility for stakeholders at different management levels in their most convenient ways by developing visual representation to display crucial information. The numerical or textual data were converted into graphics for ease of understanding for stakeholders, including field operators. The key elements for the feasible implementation of the proposed model in an industrial area were discussed. They are strategic-level components, IoT-enabled warehouse environments, customized middleware settings, real-time processing software and visual dashboard configuration.

While this study shows a prototype-based implementation of actual warehouse operations in one of Indonesia’s manufacturing companies, the architectural requirements are applicable and extensible by other companies. In this sense, the research offers significant economic advantages by using customized middleware to avoid unnecessary waste brought by the off-the-shelves generic middleware, which is not entirely suitable for system development.

This research’s finding contributes to filling the gap in the limited body of knowledge of real-time analytics implementation in warehousing operations. This should encourage other researchers to enhance and develop the devised elements to enrich smart warehousing’s theoretical knowledge. Besides, the successful proof-of-concept implementation reported in this research would allow other companies to gain valuable insights and experiences.

Rapid innovation and globalization have generated tremendous opportunities and choices in the marketplace for firms and customers. Competitive pressures have led to sourcing and manufacturing on a global scale resulting in a significant increase in products. The paper tries to identify the need for real time business intelligence (BI) in supply chain analytics.

The paper provides argument and analysis of the advantages and hurdles in BI.

The paper focuses on the necessity to revisit the traditional BI concept that integrates and consolidates information in an organization in order to support firms that are service oriented and seeking customer loyalty and retention. Enhancing effectiveness and efficiency of supply chain analytics using a BI approach is a critical component in a company's ability to achieve its competitive advantage.

This paper furthers understanding of the issues surrounding the use of BI systems in supply chains.