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Cement plays a significant part in concrete, and with the increasing demand for concrete, cement output varies day by day, allowing production to carbon dioxide emissions. As well as marble processing creates stone slurry and solid discards. These are often dumped irresponsibly on open land, polluting the soil. This improper disposal of marble waste is a major environmental concern. This study aims to propose a sustainable solution for reusing this waste material as a concrete additive.

A total of 135 concrete cubes of size 150 × 150 × 150 mm, 54 concrete cylinders of size 150 mm dia. and 300 mm height and 54 concrete beams of size 150 × 150 × 700 mm were cast. The replacement was 0%, 2.5%, 5%, 7.5%, 10%, 12.5%, 15%, 17.5% and 20% by weight of cement with marble dust to create M30 concrete with a water-cement ratio of 0.45. The test was performed to find the compressive strength (CS), flexural strength (FS) and split tensile strength. Also, durability tests like rapid chloride penetration test (RCPT), acid attack, ultrasonic pulse velocity (UPV) and water permeability test were performed.

After 7 and 28 days of curing, it was found that replacing 5% of cement with marble powder led to an initial strength improvement of up to 25% for both curing periods. However, further increases in marble dust resulted in an inconsistent decrease in strength for all the mixtures. Also, durability properties like acid attack test, water permeability test and RCPT, showed good performance at the optimum percentage of waste marble powder (WMP) as cement replacement. The microscopic analysis revealed a denser pore structure at lower WMP replacement levels, likely due to the powder filling in gaps.

This study reveals that by substituting 5% (optimum) of cement with WMP, there was CS improvement up to 8.4% and 17% for both 7 and 28 days of curing. WMP is typically finer than cement particles and fills the voids in the concrete more effectively, resulting best performance at optimum percentage against RCPT, UPV, acid attack and water permeability.

This study investigated the potential of partially replacing cement with red mud (RM) in concrete and examined its effects on its mechanical properties and microstructure. This study aims to explore sustainable alternatives to traditional cement and evaluate the performance of concrete mixtures with varying percentages (%) of RM as cement replacement.

This research aims to comprehensively understand the impact of RM on concrete, aiming for both environmental sustainability and improved construction materials. Subsequently, concrete mixtures were prepared with varying RM contents, ranging from 0% to 21% in increments of 3%, replacing cement. The workability of these mixtures was evaluated using the Slump Cone Test, whereas their mechanical properties (compressive strength, flexural strength and split tensile strength) were assessed through standardized tests. The durability was further investigated via water absorption, acid attack, rapid chloride permeability tests, open porosity test and Sorptivity test. To gain deeper insights into the internal structure of concrete, microstructure analysis was conducted using X-ray diffraction and scanning electron microscopy. Finally, the results were analyzed and quantified.

The finding demonstrates that substituting 12% of cement with RM not only boosts the mechanical characteristics of concrete but also mitigates waste disposal. The microstructural analysis identified a denser cement matrix and improved bonding between the cement paste and the aggregates, suggesting potential improvements in strength and durability.

These results suggest that RM can be efficiently used to produce sustainable concrete with potential applications in construction projects with environmental considerations.

After completion of the case study, students will be able to recall the fundamental concepts of group arrival and the check-in process within the hotel industry; explain the various operational procedures used to enhance a smooth group check-in in hotels; use the steps defined in group check-in procedure to improve service efficiency in hotel operations; and examine and evaluate the optimal solution for a smooth group check-in for hotels.

“The Big Fat Indian Wedding” delves into the challenges faced by Hotel Plaza Blu, a business hotel in Pune, Maharashtra, in 2023. A big wedding group was arriving at the hotel, which comprised almost 350 adults and 120 children. Mr Parag Patil, the front office manager, had done all the preparations for group arrival but just one hour before the arrival Mr Suresh Menon, the group coordinator, came and informed that 150 additional guests would be arriving, as the other hotel, where arrangements for these guests were made, had a major electricity generator breakdown and the hotel was in complete blackout. Patil had the challenge of formulating an action plan to achieve a smooth group check-in with the last-minute changes.

Executive development programmes and graduate-level courses in non-profit hospitality and tourism management might benefit from this case study. The operational management courses in the BBA, UG management programmes might all benefit from using this case study.

Teaching notes are available for educators only.

CSS 9: Operations and Logistics.

The case describes the performance evaluation system that has been put in place by Ravi Kumar, the MD to ensure that Oystar Hassia is able to design, deliver, service, sell its packaging machines seamlessly in all parts of the world. The performance evaluation system is periodic, regular, able to take track the progress of the people within the system. The benefits accrued from performance evaluation system are also detailed in this case.

This article intends to explore critical factors that affect the adoption of organic farming in emerging economies. The authors respond to the calls from policymakers, non-government organizations, business firms and scholars to improve the farmers' awareness of the negative impact of synthetic chemical pesticides, phosphorus, potassium fertilizers and mineral nitrogen used in traditional farming.

Through self-administered survey questionnaires, responses were obtained from 397 farmers (conventional) regarding organic farming adoption in Haryana (India). The survey responses were collected between October 2022 and December 2022. The authors apply the “partial least squares structural equation modeling” (PLS-SEM) to test the framed hypotheses.

The present article demonstrates six critical determinants of organic farming adoption, i.e. behavioral, cultivation, economic, governmental, marketing, and social factors. These six factors drive 71.0% (R²) variation in organic farming adoption. Governmental factors have a positive but insignificant influence on organic farming adoption. Interestingly, the impact of behavioral and cultivation factors is crucial per path coefficient values.

For the first time, the authors conducted a study on organic farming adoption in Haryana that lies in its context-specific implementation, utilization of localized knowledge and expertise, regional policy support, agricultural diversification and community participation. Future research can build upon by adding agriculture scientists to the study to respond to the cost, quality of the crop and impact of socio-economic policies as moderators/mediators on adoption decisions.

The purpose of this paper is to formulate frameworks for the drivers and barriers of integrated sustainable solid waste management (ISSWM) with reference to conditions prevailing in India.

A multi-phased approach was adopted in this paper to come up with the conceptual framework of the drivers and barriers of ISSWM. In the first phase, drivers and barriers of ISSWM were identified based on a systematic literature review process. In the second phase, 25 experts having 15 plus years of experience in the field of sustainable development and environmental management were consulted to get their opinion. Validation and understanding of the interrelationship among the selected drivers and barriers were done based on the insights from expert interviews. And in the final phase, structural self-interaction matrix and transitive links are defined based on the expert opinion to come up with the theoretical frameworks of drivers and barriers of ISSWM.

Findings reveal the importance to have a system view point approach by giving equal importance to social, environmental and economic pillars of sustainability along with the technology component to effectively and sustainably manage the solid waste disposal. Institutional effectiveness and the robust policy and frameworks are the two variables found to have the highest driving power. Poor social values and ethics, huge population and illiteracy are the three most critical barriers faced by developing nations in achieving the sustainability practices in the solid waste management. The proposed frameworks of drivers and barriers of ISSWM will definitely help policy makers to effectively manage the sustainable waste management practices for developing economies by focusing on the key variables listed out.

One of the limitations is in the use of very limited sample size in the study. Another limitation is that total interpretive structural modeling fails to come up with the relative weightings of drivers and barriers used in the study. These limitations can be overcome by extending the research by using a semi-structured questionnaire survey with higher sample size for the empirical validation of the model.

This research will help to clearly understand the framework of drivers and barriers of variables and their hierarchical level based on the driving power and dependence. Since such articles focusing on the conceptual frameworks of drivers and barriers of ISSWM are found to be very scant, this paper will equally help academicians and waste management professionals to understand the concepts deeply, by getting answers to the fundamental questions of “what,” “why” and “how.” Developed framework of drivers explicitly shows the need to attain financial stability through the commercialization of the waste management initiatives, which will help to reduce burden on various governmental institutions. Commercialization opportunities will also help to have more successful start-up ventures in solid waste management domain that can provide improved employment opportunities and hygiene environment in the developing nations like India.

Based on the authors’ best knowledge, there is hardly any article that explicitly explains the conceptual frameworks of the drivers and barriers of ISSWM by considering the conditions prevailing in developing countries like India. And thus, this can be considered as one of the unique research attempts to build a clear conceptual framework of ISSWM. The study contributes significantly to the existing literature body by clearly interpreting the interrelationships and the driving power and dependence of variables of ISSWM.

Artificial neural networks (ANNs), which represent computational models simulating the biological neural systems, have become a dominant paradigm for solving complex analytical problems. ANN applications have been employed in various disciplines such as psychology, computer science, mathematics, engineering, medicine, manufacturing, and business studies. Academic research on ANNs is witnessing considerable publication activity, and there exists a need to track the intellectual structure of the existing research for a better comprehension of the domain. The current study uses a bibliometric approach to ANN business literature extracted from the Web of Science database. The study also performs a chronological review using science mapping and examines the evolution trajectory to determine research areas relevant to future research. The authors suggest that researchers focus on ANN deep learning models as the bibliometric results predict an expeditious growth of the research topic in the upcoming years. The findings reveal that business research on ANNs is flourishing and suggest further work on domains, such as back-propagation neural networks, support vector machines, and predictive modeling. By providing a systematic and dynamic understanding of ANN business research, the current study enhances the readers' understanding of existing reviews and complements the domain knowledge.

Social media platform, like Twitter, has increasingly become the mode of reporting civic issues owing to their vast and fast reachability. A tremendous amount of information on urban issues is shared every moment out of which some tweets may need immediate attention to save lives or avoid future disasters. Existing approaches are only limited to the identification of complaint tweets; however, its prioritization based on urgency is still unexplored. This study aims to decide the ranking of complaints based on its criticality derived using multiple parameters, like type of complaint, season, day or night, gender, holiday or working day, etc.

The approach proposes an ensemble of multi-class classification (MCC) and “two-level” multi-criteria decision-making (MCDM) algorithms, like AHP and TOPSIS, to evaluate the accurate ranking score of the tweet based on the severity of the issue. Initially, the MCC is applied to tweets to categorize the tweets into three categories, i.e. moderate, urgent and immediate. Further, the first level of MCDM algorithm decides the ranking within each complaint type, and the second level evaluates the ranking across all types. Integration of MCC and MCDM methods further helps to increase the accuracy of the result.

The paper discusses various parameters and investigates how their combination plays a significant role in deciding the priority of complaints. It successfully demonstrates that MCDM techniques are helpful in generating the ranking score of tweets based on various criteria.

This paper fulfills an identified need to prioritize the complaint tweet which helps the local government to take time-bound actions and save a life.

This chapter addresses one aspect of the broad issue of the psychological foundations of the dimensions of multidimensional scaling (MDS) solutions. Using empirical data from three independent studies, it is shown that the dimensionality of MDS solutions is negatively related to individual differences in the level of cognitive differentiation and integrative complexity of individuals and positively related to the individual's ability to discriminate within dimensions. MDS dimensionality is also shown to be affected by a variety of task-related variables such as perceived task difficulty, consistency in providing similarity judgments, confidence, familiarity, and importance attached to the stimuli. The chapter concludes by raising the issue of whether MDS can be validly used to describe complex cognitive processes.

The purpose of this paper is to share knowledge of how annotation can be the basis for knowledge sharing.

The method used was derived from mathematical methods applied to set theory.

It was presented that one document can be easily used for experience sharing with multiple users. Multiple documents will be difficult to use as source of experience sharing.

Experience sharing has never been presented as intersection of annotation, document and users using mathematic principles.