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This paper aimed at identifying the effects of atmosphere on the consumer purchase intention in international retail chain outlets of Karachi, Pakistan. This was the first study, which investigated the collective impact of atmospheric variables at one point in time on purchase intention. This research was causal in nature. A sample of 300 consumers was taken who usually visited these outlets. Data was collected through a well-structured questionnaire and analyzed through regression analysis. Research findings indicate that atmospheric variables such as cleanliness, scent, lighting, and display/layout have a positive influence on consumers' purchase intention; whereas music and color have insignificant impact on consumers' purchase intention. The temperature has almost no impact on the purchase intention of the consumers. This study has important implication for Practitioners and Academicians.

This paper aimed at identifying the effects of atmosphere on the consumer purchase intention in international retail chain outlets of Karachi, Pakistan. This was the first study, which investigated the collective impact of atmospheric variables at one point in time on purchase intention. This research was causal in nature. A sample of 300 consumers was taken who usually visited these outlets. Data was collected through a well-structured questionnaire and analyzed through regression analysis. Research findings indicate that atmospheric variables such as cleanliness, scent, lighting, and display/layout have a positive influence on consumers' purchase intention; whereas music and color have insignificant impact on consumers' purchase intention. The temperature has almost no impact on the purchase intention of the consumers. This study has important implication for Practitioners and Academicians.

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Fog devices are beginning to play a key role in relaying data and services within the Internet-of-Things (IoT) ecosystem. These relays may be static or mobile, with the latter offering a new degree of freedom for performance improvement via careful relay mobility design. Besides that, power conservation has been a prevalent issue in IoT networks with devices being power-constrained, requiring optimal power-control mechanisms. In this paper, we consider a multi-tier fog-based IoT architecture where a mobile/static fog node acts as an amplify and forward relay that transmits received information from a sensor node to a higher hierarchically-placed static fog device, which offers some localized services. The outage probability of the presented scenario was efficiently minimized by jointly optimizing the mobility pattern and the transmit power of the fog relay. A closedform analytical expression for the outage probability was derived. Furthermore, due to the intractability and non-convexity of the formulated problem, we applied an iterative algorithm based on the steepest descent method to arrive at a desirable objective. Simulations reveal that the outage probability was improved by 62.7% in the optimized-location fixed-power (OLFP) scheme, 79.3% in the optimized-power fixed-location (OPFL) scheme, and 94.2% in the optimized-location optimized-power (OLOP) scheme, as against the fixed-location and fixed-power (FLFP) scheme (i.e., without optimization). Lastly, we present an optimal relay selection strategy that chooses an appropriate relay node from randomly distributed relaying candidates.

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Finding holes from the underutilized portion of spectrum at various times and locations is the most important function in cognitive radio networks (CRNs). This requires efficient sensing policy at the MAC layer that can discover more idle channels in less time. Whereas, the sensing policy depends on the channel sensing order that decides how a secondary user senses the primary user band in minimum period of time. Spectrum sensing policies for searching idle channels from the underutilized primary band can significantly affect the performance of secondary user in terms of throughput, reliability, and energy efficiency. In this paper, we have analyzed MAC protocol structure for ad hoc radio networks which used random channel sensing. This results in poor performance, either due to the channels being skipped or the time for sensing the band being significantly longer. We propose a parallel sensing scheme with sequential channel selection order as part of MAC protocol, which can discover all the free channels in the primary user band in less time. For the proposed scheme, we have performed analysis over the number of channels sensed and the number of idle channels discovered. Furthermore, energy efficiency and throughput of the system have also been evaluated. The results show considerable improvement for the proposed scheme when compared with the contemporary scheme.