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Not that long ago, half of all sales research was demonstrably if not unequivocally “atheoretical” (Williams and Plouffe, 2007). The foundational argument of this paper is that stronger theoretical development and application of theory in sales research is critical for the sales field to retain its relevancy. The purpose of this paper is to underscore that deliberate and cogent application of HWV (2018) is scant in the recent sales literature (over five years after publication in Journal of Marketing) for one or both of two reasons: scholars either do not understand the paper and/or are fearful of (mis)applying it.

More than simply introducing the articles to this special issue of the European Journal of Marketing (EJM), this paper also makes a number of important, overdue contributions. Although Hartmann, Wieland and Vargo’s JM (HWV, 2018) theoretical and conceptual paper has been well-received by the sales community, it has seen limited meaningful integration or application in sales research since its publication. This paper thus clarifies key misunderstandings and misperceptions with HWV (2018) so that sales researchers can more impactfully apply it to future sales research.

This paper identifies and then explains key aspects of service-dominant logic (S-D logic) and commonly misapplied and/or misunderstood aspects of HWV (2018) to guide future sales research. Ultimately, the overarching goal of this special issue of EJM is to focus a “spotlight” on sales theory development, while simultaneously demonstrating – through the five articles the special issue reports – that with purposeful effort, rich theoretical insights can effectively be applied to both “classic” and more current and emergent sales research topics.

Because HWV (2018) draw heavily upon S-D logic, it follows that some aspects of their article have been misinterpreted or misapplied by sales scholars. In particular, the critical concept of “crossing points” (both of the “thick” and “thin” variety) are explicated and detailed further, so as to afford sales researchers with better knowledge and insight on how to apply these key tools within HWV (2018).

The practical implications of this paper primarily revolve around further educating and clarifying for sales researchers “how” to better apply HWV (2018) to sales research, rather than simply citing it in passing. The paper also concludes by providing a summary and introduction to each of the five EJM special issue articles.

The originality and value of this paper and this special issue of the EJM is twofold. First, both this paper and the entire special issue itself emphasize the ongoing importance of advancing sales research through the meaningful and cogent application of theory. Second, the paper demonstrates that purposeful effort can lead to successful applications of HWV (2018) – as exhibited by the five articles in the EJM special issue – such that rich theoretical insights can be woven into both traditional and contemporary sales research topics.

Electric motor heating during biomass recovery and its handling on conveyor is a serious concern for the motor performance. Thus, the purpose of this paper is to design and develop a hardware prototype of master–slave electric motors based biomass conveyor system to use the motors under normal operating conditions without overheating.

The hardware prototype of the system used master–slave electric motors for embedded controller operated robotic arm to automatically replace conveyor motors by one another. A mixed signal based embedded controller (C8051F226DK), fully compliant with IEEE 1149.1 specifications, was used to operate the entire system. A precise temperature measurement of motor with the help of negative temperature coefficient sensor was possible due to the utilization of industry standard temperature controller (N76E003AT20). Also, a pulse width modulation based speed control was achieved for master–slave motors of biomass conveyor.

As compared to conventional energy based mains supply, the system is self-sufficient to extract more energy from solar supply with an energy increase of 11.38%. With respect to conventional energy based \ of 47.31%, solar energy based higher energy saving of 52.69% was reported. Also, the work achieved higher temperature reduction of 34.26% of the motor as compared to previous cooling options.

The proposed technique is free from air, liquid and phase-changing material based cooling materials. As a consequence, the work prevents the wastage of these materials and does not cause the risk of health hazards. Also, the motors are used with their original dimensions without facing any leakage problems.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

Nowadays, food problems are likely to arise because of the increasing global population and decreasing arable land. Therefore, it is necessary to increase the yield of agricultural products. Pesticides can be used to improve agricultural land products. This study aims to make the spraying of cherry trees more effective and efficient with the designed artificial intelligence (AI)-based agricultural unmanned aerial vehicle (UAV).

Two approaches have been adopted for the AI-based detection of cherry trees: In approach 1, YOLOv5, YOLOv7 and YOLOv8 models are trained with 70, 100 and 150 epochs. In Approach 2, a new method is proposed to improve the performance metrics obtained in Approach 1. Gaussian, wavelet transform (WT) and Histogram Equalization (HE) preprocessing techniques were applied to the generated data set in Approach 2. The best-performing models in Approach 1 and Approach 2 were used in the real-time test application with the developed agricultural UAV.

In Approach 1, the best F1 score was 98% in 100 epochs with the YOLOv5s model. In Approach 2, the best F1 score and mAP values were obtained as 98.6% and 98.9% in 150 epochs, with the YOLOv5m model with an improvement of 0.6% in the F1 score. In real-time tests, the AI-based spraying drone system detected and sprayed cherry trees with an accuracy of 66% in Approach 1 and 77% in Approach 2. It was revealed that the use of pesticides could be reduced by 53% and the energy consumption of the spraying system by 47%.

An original data set was created by designing an agricultural drone to detect and spray cherry trees using AI. YOLOv5, YOLOv7 and YOLOv8 models were used to detect and classify cherry trees. The results of the performance metrics of the models are compared. In Approach 2, a method including HE, Gaussian and WT is proposed, and the performance metrics are improved. The effect of the proposed method in a real-time experimental application is thoroughly analyzed.

The purpose of this study is to plan and develop a cost-effective health-care robot for assisting and observing the patients in an accurate and effective way during pandemic situation like COVID-19. The purposed research work can help in better management of pandemic situations in rural areas as well as developing countries where medical facility is not easily available.

It becomes very difficult for the medical staff to have a continuous check on patient’s condition in terms of symptoms and critical parameters during pandemic situations. For dealing with these situations, a service mobile robot with multiple sensors for measuring patients bodily indicators has been proposed and the prototype for the same has been developed that can monitor and aid the patient using the robotic arm. The fuzzy controller has also been incorporated with the mobile robot through which decisions on patient monitoring can be taken automatically. Mamdani implication method has been utilized for formulating mathematical expression of M number of “if and then condition based rules” with defined input X_j (j = 1, 2, ………. s), and output y_i. The inputs and output variables are formed by the membership functions µ_Aij(x_j) and µ_Ci(y_i) to execute the Fuzzy Inference System controller. Here, Aij and Ci are the developed fuzzy sets.

The fuzzy-based prediction model has been tested with the output of medicines for the initial 27 runs and was validated by the correlation of predicted and actual values. The correlation coefficient has been found to be 0.989 with a mean square error value of 0.000174, signifying a strong relationship between the predicted values and the actual values. The proposed research work can handle multiple tasks like online consulting, continuous patient condition monitoring in general wards and ICUs, telemedicine services, hospital waste disposal and providing service to patients at regular time intervals.

The novelty of the proposed research work lies in the integration of artificial intelligence techniques like fuzzy logic with the multi-sensor-based service robot for easy decision-making and continuous patient monitoring in hospitals in rural areas and to reduce the work stress on medical staff during pandemic situation.

The purpose of this study is to investigate the impact of integrating “Licorice powder” into curd balls on their storage stability under refrigeration conditions. Through this examination, this study aims to evaluate the potential effects of licorice powder on extending the shelf life, maintaining quality attributes and preserving the overall stability of curd balls when stored at refrigeration temperatures.

Licorice powder, in varying quantities (1%, 2% and 3%), was incorporated into curd balls alongside a control group lacking licorice (0%). These batches were subsequently stored for 25 days under refrigeration at a temperature of 4 ± 1ºC, using aerobic packaging conditions. During this storage period, the samples were regularly monitored and analyzed for various parameters to assess changes in their properties and qualities.

The findings indicated that in the treatment groups, pH and titratable acidity were notably lower than those in the control group (p = 0.05). Curd balls enriched with licorice powder exhibited significantly higher levels of 2, 2-diphenyl-1-picrylhydrazyl, 2-2-azinobis-3ethylbenthiazoline-6-sulphonic acid and total phenolic contents compared to the control (p = 0.05). Furthermore, curd balls containing licorice powder displayed notably lower levels of peroxide, thiobarbituric acid reactive substances and free fatty acids in comparison to the control (p = 0.05). Among all samples, T3 (3%) demonstrated significantly less microbial growth (p = 0.05) than the other groups. Conversely, the sensory panel rated T2 significantly higher than T3 (p = 0.05).

The investigation highlights that curd balls enriched with 2.0% licorice powder demonstrated significant efficacy in preventing the deterioration of physicochemical attributes, enhancing antioxidant capacity, restraining lipid oxidation, curbing microbial growth and ultimately exhibiting the most favorable organoleptic properties among the tested variations. This finding underscores the potential of incorporating 2.0% licorice powder as an effective agent for bolstering the storage stability and overall quality of curd balls during refrigerated storage.

This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.

Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.

ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.

IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.

Tourism destination marketers use videos that incorporate storytelling and visual and audio components to evoke emotional arousal and memorability. This study aims to examine the increase in participants’ level of arousal and the degree of memorability after watching two different videos.

A quasi-experimental study was conducted with 45 participants who watched two destination promotional videos. One video used storytelling whereas the other used scenic images and music. The level of arousal was measured using both tonic and phasic electrodermal activity levels. The memorability of each video was measured after seven days by testing the recall accuracy.

Scenic imagery and music videos were associated with higher-than-average arousal levels, while storytelling videos generated larger-amplitude arousal peaks and a greater number of arousal-evoking events. After a week, the respondents recalled more events from the storytelling video than from the scenery and musical advertisements. This finding reveals that the treatment, storytelling and sensory stimuli in advertising moderate the impact of arousal peaks and memorability.

These results indicate that nonnarrative videos using only sceneries and music evoked a higher average level of arousal. However, memorability was associated with higher peak levels of arousal only in narrative storytelling. This is the first tourism study to report the effects of large arousal peaks on improved memorability in advertising.

Most companies struggle to meet the dual goals of sustaining competitive advantage and ensuring high resilience during crises. Those that do, research tells, adapt their operational practices along the crisis cycle, combining an effective cost approach at the start of a crisis, while quickly relaunching their investment to grow ahead of competition, just when they learn that the crisis is peaking, and not too late, when the crisis is over. This cycle alignment is possibly the crucial, but not the only, factor for success. We update early research to show that companies succeeding in this dual objective also take a proactive strategy approach of capturing the complementarities between both performance and resilience during a period of high turbulence. This complementarity relies on exploiting dynamic capabilities common to both resilience and performance, and on leveraging the resilience process as a foundation for strategic renewal going forward.

The research relies on case studies, complemented by an original survey sample, collected just after the peak of the covid-19 pandemic, of 4,000 multinational firms spread across 18 industries termed NACE2, a statistical classification of economic activities in the European Community. This study included 10 countries outside the European Community. The sample collects information on five core enterprise capabilities (agility, innovativeness, active ecosystem play and digital/sustainability maturity, flexible work practices) and uses a variety of quantitative techniques to assess that existence and size of synergies captured by firms.

Companies meeting the dual goal of resilience and performance are more than doubling their rate of profit growth relatively to peers, after the peak of the crisis, by leveraging of synergies between performance and resilience.

The topic is essential for management, given the elevated turbulence. This research confirms that resilience and performance are synergistic and helps make companies using each crisis boost performance forward.

This study aims to highlight that security and flexibilities remain the main points of contention in the cordiality business. This research points to planning a framework that empowers hotel users to get to the room using a mobile access key. Advancing secured facilities, mobile phone “Near Field Communication” (NFC) innovation as the entrance device by carrying out an application containing an imitated mobile key for explicit verification access is used.

The proposed system is evaluated by triangulation of experimental, numerical and rational evaluation using partial least square structural equation modeling (PLS-SEM) with Malaysian hotel guests and employees.

The discoveries with the hypothesis supported validated that the suggested solution can eliminate physical cards, boost protection and encourage a contactless ecosystem. Theoretical, management and societal contributions are discussed here.

This experiment comes with the constraints that it was conducted in only two hotels and does not fully reflect the choices of a wider range of travellers. Secondly, the cost of existing NFC smart locks is still relatively high, and along with the development of technology, the price will decrease when supply exceeds demand.

To promote high-security attributes, NFC technology as the access system by implementing an application containing an emulated smart key for specific authentication access is used. The host-card emulation enables cost-effectiveness profit and initiating a defence system in the pandemic era.

To promote high-security attributes, NFC technology is used as the access system by implementing an application containing an emulated smart key for specific authentication access. The host-card emulation enables cost-effectiveness profit and initiating a defence system in the pandemic era.

The novelty of this study comes from the use of commonly available smartphone NFC features that are yet to be applied in the tourism ecosystem. The research provokes the applied concept of mobile smartkeys.