Alireza Golabchi, Manu Akula and Vineet Kamat
Organizations involved in facility management (FM) can use building information modeling (BIM) as a knowledge repository to document evolving facility information and to support…
Abstract
Purpose
Organizations involved in facility management (FM) can use building information modeling (BIM) as a knowledge repository to document evolving facility information and to support decisions made by the facility managers during the operational life of a facility. Despite ongoing advances in FM technologies, FM practices in most facilities are still labor intensive, time consuming and often rely on unreliable and outdated information. To address these shortcomings, the purpose of this study is to propose an automated approach that demonstrates the potential of using BIM to develop algorithms that automate decision-making for FM applications.
Design/methodology/approach
A BIM plug-in tool is developed that uses a fault detection and diagnostics (FDD) algorithm to automate the process of detecting malfunctioning heating, ventilation, and air conditioning (HVAC) equipment. The algorithm connects to a complaint ticket database and automates BIM to determine potentially damaged HVAC system components and develops a plan of action for the facility inspectors accordingly. The approach has been implemented as a case study in an operating facility to improve the process of HVAC system diagnosis and repair.
Findings
By implementing the proposed application in a case study, the authors found that automated BIM approaches such as the one developed in this study, can be highly beneficial in FM practices by increasing productivity and lowering costs associated with decision-making.
Originality/value
This study introduces an innovative approach that leverages BIM for automated fault detection in operational buildings. FM personnel in charge of HVAC inspection and repair can highly benefit from the proposed approach, as it eliminates the time required to locate HVAC equipment at fault manually.
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Purva Grover, Arpan Kumar Kar and Marijn Janssen
Although blockchain is often discussed, its actual diffusion seems to be varying for different industries. The purpose of this paper is to explore the blockchain technology…
Abstract
Purpose
Although blockchain is often discussed, its actual diffusion seems to be varying for different industries. The purpose of this paper is to explore the blockchain technology diffusion in different industries through a combination of academic literature and social media (Twitter).
Design/methodology/approach
The insights derived from the academic literature and social media have been used to classify industries into five stages of the innovation-decision process, namely, knowledge, persuasion, decision, implementation and confirmation (Rogers, 1995).
Findings
Blockchain is found to be diffused in almost all industries, but the level of diffusion varies. The analysis highlights that manufacturing industry is at the knowledge stage. Further public administration is at persuasion stage. Subsequently, transportation, communications, electric, gas and sanitary services and trading industry had reached to the decision stage. Then, services industries have reached to implementation stage while finance, insurance and real estate industries are the innovators of blockchain technologies and have reached the confirmation stage of innovation-decision process.
Practical implications
Actual implementations of blockchain technology are still in its infancy stage for most of the industries. The findings suggest that specific industries are developing specific blockchain applications.
Originality/value
To the best of the authors’ knowledge this is the first study which is using social media data for investigating the diffusion of blockchain in industries. The results show that the combination of Twitter and academic literature analysis gives better insights into diffusion than a single data source.
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Worachet Onngam and Peerayuth Charoensukmongkol
The purpose of this study was to analyze the effects of social media analytics on firm performance using a sample of small and medium enterprises (SMEs) in Thailand. This study…
Abstract
Purpose
The purpose of this study was to analyze the effects of social media analytics on firm performance using a sample of small and medium enterprises (SMEs) in Thailand. This study also investigated whether entrepreneurial orientation (EO) moderated the effects of social media analytics on firm performance.
Design/methodology/approach
This study used SMEs listed in the Department of Business Development of Thailand as the sampling frame. Probability sampling was used to draw the sample. A questionnaire survey was used to collect data from 334 firms. The data were analyzed using partial least squares structural equation modeling.
Findings
The results supported the positive association between social media analytics practices on firm performance. Moreover, this study found that EO moderated this association significantly. In particular, the positive association between social media analytics practices on firm performance was higher for firms that exhibit a high EO than those that exhibit a low EO. This result indicated that firms that implement social media analytics practices achieved higher performance when they exhibited a high EO.
Practical implications
Social media data analytics should be implemented to strengthen the technological competence of firms. Moreover, firms should integrate EO practices into their implementation of social media analytics to increase their ability to generate substantial improvements in their strategic implementation, thereby enabling them to gain sustainable competitiveness in their market.
Social implications
Because SMEs are the driving force for economic growth and development in Thailand, their ability to achieve higher performance when they effectively integrate EO practices into their implementation of social media data analytics could be beneficial for the sustainable development of Thailand, especially in the current data-driven era.
Originality/value
The result that EO moderates the effect in enhancing social media analytics practices’ influence on firm performance provides new knowledge that extends the boundary of research on this topic. The authors provided a theoretical explanation to clarify the way the implementation of social media analytics practices should be integrated with EO to increase the level of performance that firms achieve from such practices.