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This study aims to examine how perceived brand credibility (PBC) moderates the adoption of the Internet of Things (IoT) and identifies the influencing variables that consumers consider while adopting IoT products and services. The study uses the technology acceptance model (TAM) and extends its constructs by investigating the role of PBC to measure the intention to use IoT.

To test the proposed relationships, data was gathered using the survey method, from respondents in India, an emerging market. The data was analyzed using partial least square based structural equation modeling (PLS-SEM). Moreover, the study measured the moderating effect of PBC and evaluated the effect of control variables – gender and degree of exposure to IoT.

The study found that perceived usefulness (PU) and perceived ease of use (PEOU) have a significant influence on customers’ attitudes towards using IoT devices and services. Further, PBC moderates the relationship between attitude and behavioral intention to utilize IoT devices and services. Both components of PBC – brand trustworthiness and trust – have significant moderating effect on the adoption of IoT-based services and devices.

The study tests TAM empirically in a new setting and extends it further. Introducing PBC as a moderating variable improves the understanding of the way consumers adopt IoT technology and hence strengthens the predictive power of TAM. Thus, the study provides rich insights for businesses to effectively position their IoT devices and services among their target users.

This research presents a study on the supply chain process of an Indian apparel industry considering various parameters involved. The study aims to identify the main parameters to improve the supply chain process and develop a comprehensive structural relationship to rank them to streamline the apparel supply chain process and business environment.

The team of five experts from this apparel industry was made to give scores to multiple parameters. The TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) technique is used to develop the model for eleven key parameters and then rank them.

Based on the data analysis the planning, customer and warehouse storage have emerged as top three key parameters while the non-replenishment approach, push and pull strategy and manufacturing of the product are identified as the bottom three parameters from a hierarchy level. These parameters have been ranked based on their contributing attributes in this apparel supply chain process.

The study provides an overall ranking of parameters and the implications are in the direction of helping the industry to improve its supply chain performances rather than focus only on productivity. Further, the key parameters are identified as critical inputs and show that the firms are being more proactive and well prepared comprised of the industry.

The study indicates that the key parameters are identified by this apparel brand to improve its supply chain process. The key supply chain process involves planning, manufacturing, distribution, end customer and returns logistics of the goods, etc. So, this research also provides the focused parameters on the supply chain performance received by end customer from the supplier and rank them for effectiveness and improve their overall organizational performance. It also provides a critical observation of their supply chain process improvement which includes different brand uses, strategies and approaches.