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The purpose of this paper is to study lightweight security scheme for Internet of Things (IoT) applications using Constrained Application Protocol (CoAP). Resource-constrained characteristics of IoT systems have ushered in compelling requirements for lightweight application protocol and security suites. CoAP has already been established as the candidate protocol for IoT systems. However, low overhead security scheme for CoAP is still an open problem. Existing security solutions like Datagram Transport Layer Security (DTLS) is not suitable, particularly due to its expensive handshaking, public key infrastructure (PKI)-based authentication and lengthy ciphersuite agreement process.

This paper proposes a lightweight security scheme in CoAP using Advanced Encryption Standard (AES) 128 symmetric key algorithm. The paper presents an object security (payload embedded)-based robust authentication mechanism with integrated key management. The paper introduces few unique modifications to CoAP header to optimize security operation and minimize communication cost.

It is resilient to number of security attacks like replay attack, meet-in-the-middle attack and secure under chosen plaintext attack. This scheme is generic in nature, applicable for gamut of IoT applications. The paper proves efficacy of our proposed scheme for vehicle tracking application in emulated laboratory setup. Specifically, it compares with DTLS-enabled CoAP to establish the lightweight feature of our proposed solution.

This paper mainly focuses on implementing in-vehicle tracking systems as an IoT application and used CoAP as the application protocol.

Such a lightweight security scheme would provide immense benefit in IoT systems so that resource constraint-sensing devices and nodes can be made secure. This would impact IoT eco systems to a large extent.

Such kind of security suite that provides both robustness and lightweight feature is hitherto not known to the authors, particularly in CoAP for IoT applications.

The purpose of this paper is to identify the factors influencing the citizens of India to prevent cybercrimes in the proposed Smart Cities of India.

A conceptual model has been developed for identifying factors preventing cybercrimes. The conceptual model was validated empirically with a sample size of 315 participants from India. Data were analyzed using structural equation modeling with SPSS and AMOS softwares.

The study reveals that the “awareness of cybercrimes” significantly influences the actual usage of technology to prevent cybercrimes in Smart Cities of India. The study reveals that government initiative (GI) and legal awareness are less influential in spreading of the awareness of cybercrimes (AOC) to the citizens of the proposed smart cities.

The conceptual model utilizes two constructs from the technology adoption model, namely, perceived usefulness and ease of use. The study employs other factors such as social media, word of mouth, GIs, legal awareness and organizations constituting entities spreading awareness from different related literature works. Thereby, a comprehensive theoretical conceptual model has been proposed which helps to identify the factors that may help in preventing cybercrimes.

This study provides an insight to the policy maker to understand several factors influencing the AOC of the citizens of the proposed Smart Cities of India for the prevention of cybercrimes.

There are few existing studies analyzing the effect of AOC to mitigate cybercrimes. Thus, this study offers a novel contribution.

In the heated debate about marketing globalization, the issue of brand standardization has received much less attention compared with advertising standardization. When both issues have been addressed, empirically or conceptually, they have not been considered simultaneously. The current study develops and empirically tests a framework to simultaneously consider brand and advertising standardization strategies. A survey was conducted among brand managers in firms operating in Canada, with data collected on a brand level. The results revealed an independence of brand and advertising standardization practices. It was also found that brand standardization was practised to a much higher degree than advertising standardization, with the most used combined strategy involving brand name standardization and non‐standardization of advertising. Effects of product type and brand age were also investigated. The findings clearly indicate that companies tend to “brand globally, advertise locally”.

Given the heated academic and policy debate regarding the fate of garment manufacturing in a high-wage developed economy in the 21st century, this study aims to explore the production and export strategies of apparel “Made in Ireland.”

A logistic regression analysis of 4,000 apparel items at the stock keeping unit (SKU) level sold in the market from January 2018 to December 2021 was conducted to evaluate the production and export strategy of apparel “Made in Ireland” versus foreign-made imported items sold in Ireland.

The statistical results showed that Ireland’s apparel manufacturing sector survived the market competition by leveraging non-price competing factors, such as distinct product assortment, cultural heritage, history and traditional craftsmanship.

The findings challenged the conclusions of the classic trade and economic development theories regarding the trajectory of the garment manufacturing sector and called for a rethink about the strategies for expanding garment manufacturing in a high-wage developed country in today’s global economy.

Live Streaming Marketing has emerged as a transformative medium, facilitating real-time product promotion and brand messaging and reshaping consumer engagement. However, knowledge of the impact of Store Atmospheric cues within live streaming contexts remains scarce. This research delves into the dynamic interplay between streamers and viewers across diverse live streaming platforms, with a focus on the impact of distinct atmospheric cues. It also seeks to explore prosocial behavior and integrate elements of social comparison theory.

We conducted semi-structured interviews with 14 streamers and 26 viewers. Participants who were active on streaming platforms and had experience of multiple live streaming sessions were purposively identified. The thematic coding approach and NVivo 12 software were employed to gain a nuanced understanding of live streaming dynamics.

Our findings highlight the significant role of emerging atmospheric cues in shaping immersive streaming experiences and fostering prosocial behavior. Additionally, we observed three formats of upward social comparisons between streamers and viewers, wherein viewers compared themselves with streamers and peers, and streamers engaged in comparisons with more experienced counterparts. This finding contributes to a sense of digital community and positive interactions because of live streaming adoptions.

By extending the application of social comparison theory, this study provides valuable insights for practitioners and scholars, enriching the understanding of both streamers’ and viewers’ psychological behavior and the dynamics of virtual retail settings.

For some specific multi-criteria decision-making (MCDM) problems, especially in emergency situations, because of the feature of criteria and other fuzzy factors, it is more appropriate that values of different criteria are expressed in their correspondingly appropriate value types. The purpose of this paper is to build a multi-criteria group decision-making (MCGDM) model dealing with heterogeneous information based on distance-based VIKOR to solve emergency supplier selection in practice appropriately and flexibly, where a compromise solution is more acceptable and suitable.

This paper extends the classical VIKOR to a generalized distance-based VIKOR to handle heterogeneous information containing crisp number, interval number, intuitionistic fuzzy number and hesitant fuzzy linguistic value, and develops an MCGDM model based on the distance-based VIKOR to handle the multi-criteria heterogeneous information in practice. This paper also introduces a parameter called non-fuzzy degree for each type of heterogeneous value to moderate the computation on aggregating heterogeneous hybrid distances.

The proposed distance-based model can handle the heterogeneous information appropriately and flexibly because the computational process is directly operated on the heterogeneous information based on generalized distance without a transformation process, which can improve the decision-making efficiency and reduce information loss. An example of emergency supplier selection is given to illustrate the proposed method.

This paper develops an MCGDM model based on the distance-based VIKOR to handle heterogeneous information appropriately and flexibly. In emergency supplier selection situations, the proposed decision-making model allows the decision-makers to express their judgments on criteria in their appropriate value types.