Market Segmentation

The study examined the association between customers' loyalty and the sales promotion of Nigerian Brewery. Survey research was employed for the study. Data for the study were generated from the questionnaire administered to the respondents (staff of the Brewery). The hypotheses were tested using Pearson's Product Moment Correlation Coefficient at 0.05 level of significance with aid of Statistical Package for Social Sciences (SPSS), version 20.0. Findings of the study revealed that there is a significant relationship between corporate image loyalty and sale promotion of Nigerian Brewery. It was also found out that a significant relationship exist between behavioural loyalty and sale promotion of Nigerian Brewery. Based on the findings, the study recommended among others, that strategies that boost emotional loyalty, such as product adverts should always strive to be in line with product functionality; and salespeople should always be encouraged to base arguments on actual product functions, not fictitious claims.

This evaluation of the operation of Selective Financial Assistance (SFA) follows on from that undertaken by Harris et al.,(2002) for the period 1983-84 to 1996-97. To evaluate the effectiveness of the operation of the SFA Scheme in the period April 1998 to March 2004, the research team adopted a substantially different methodology which encompassed a variety of approaches ranging from econometric 'selection'and 'assistance'modelling to face-to-face interviews with SFA Scheme beneficiaries. The Harris et al.,(2002) evaluation relied upon ...

We study a product-line price optimization problem with demand given by a discrete mixed multinomial logit (MMNL) model. The market is divided into a finite number of market segments, with product demand in each segment governed by the multinomial logit (MNL) model. We show that the concavity property with respect to the choice probability vector shown for the MNL model breaks down under MMNL even for entirely symmetric price sensitivities. In addition, the equal markup property identified for the MNL model no longer holds under MMNL, suggesting that heterogeneity in customer population justifies non-equal-markup pricing. In this paper, we characterize the profit function under MMNL as the sum of a set of quasiconcave functions and present efficient optimization algorithms. We demonstrate the application of our methods using data from Intel Corporation. Our results show that the optimal prices exploit segment differences through redistribution of sales and profit among customer segm...

Th is paper presents a fuzzy multi-attribute decision making approach for evaluating the service quality of the hotels of an important tourist destination island: Gran Canaria. We fi rst extract the information provided in www.tripadvisor.com which is becoming one of the most popular websites that assists customers in gathering travel information. Th e information provided for the hotels located on the island of Gran Canaria using the fi xed seven attributes is obtained. Service quality is a composite of these seven attributes, evaluated in a 5 point Likert scale, which are intangible and diffi cult to measure. For this reason, a method based on Fuzzy Logic is proposed using Fuzzy Numbers (FN). Triangular fuzzy numbers and fuzzy set theory is a very powerful tool to overcome some linguistic problems associated with the Likert scales. Based on the concept of the degree of optimality, we also develop through TOPSIS an overall service performance index for each hotel included in the sample. Th is index could be used by diff erent stakeholders for understanding and analyzing their relative ranking position and the level of quality provided by the hotels in a specifi c area. Finally, the ranking is analyzed according to the standard star classifi cation system fi nding that the hotel industry provides more quality than the extra-hotel industry.

Brain tumor is an anomalous proliferation of cells in the brain that can evolve
to malignant and benign tumors. Currently, segmentation of brain tumor is
the most important surgical and pharmaceutical procedures. However, manually
segmenting brain tumors is hard because it is hard to find erratically
shaped tumors with only one modality; the MRI modalities are integrated to
provide multi-modal images with data that can be utilized to segment tumors.
The recent developments in machine learning and the accessibility of medical
diagnostic imaging have made it possible to tackle the challenges of segmenting
brain tumors with deep neural networks. In this work, a novel Shuffled-
YOLO network has been proposed for segmenting brain tumors from multimodal
MRI images. Initially, the scalable range-based adaptive bilateral filer
(SCRAB) pre-processing technique was used to eliminate the noise artifacts
from MRI while preserving the edges. In the segmentation phase, we propose
a novel deep Shuffled-YOLO architecture for segmenting the internal tumor
structures that include non-enhancing, edema, necrosis, and enhancing
tumors from the multi-modality MRI sequences. The experimental fallouts
reveal that the proposed Shuffled-YOLO network achieves a better accuracy
range of 98.07% for BraTS 2020 and 97.04% for BraTS 2019 with very minimal
computational complexity compared to the state-of-the-art models.

This was one chapter in life that I thought would be without any torn out pages, but the pages got torn out at rewritten time and again. Today, this chapter is finally finished and, looking back, I realise that the torn out pages were worth the effort. I would have never been able to be the author of this work without the following people, whom I would like to thank: My Heavenly Father who gave me the strength, capability, perseverance, energy, patience and sense of humour to complete this study. My supervisor, Prof. Melville Saayman. Thank you for having faith in me and helping me to see the bigger picture. I really appreciate all your time, inputs, patience, shared knowledge, support and guidance. My assistant supervisor, Prof. Andrea Saayman for lending a hand with the data and reminding me to see things from a different point of view. A special thanks to my mother, both my sisters and Lize-Marí. Thank you for all your prayers, support, understanding, love, jokes and for believing in me when the pages of the chapter got torn out. You got me through the tough times. The fieldworkers for handing out the questionnaires at the different wine farms, especially Cindy Rootenberg and Elanie Cross. Thank you for your help and the special memories. To my colleagues, Karen Williams and Corné Heyns for giving me direction, encouragement and for your motivation. Liezl de Beer, thank you for allowing me to take the time to finish the study, your support and for always lending an ear. To all of my friends, especially Jean for having faith in my ability to finish this life chapter. Thank you for your care, support and precious friendship.

Literature indicates that events like a wine festival have many role players involved that need each other for them to be successful. The more role players there are, the more complex the event becomes, as in the case of the Wacky Wine Festival which is spread over 48 wine farms. The most important role players are the visitors and wine farmers that represent the demand and supply side of the festival. Local enterprises, wine farmers and the festival organisers put a lot of effort into the event, such as their time, money and skills. It is essential for these role players to know that they will get a return on their investment and for the host community to know that the festival will make a contribution to their local economy. Furthermore, literature indicates that the festival can improve the economic position of the role players by targeting the high spending market through intensive marketing that focuses on this particular segment. Therefore, the purpose of this study was to det...

This research was caused by the changing environment and other supporting factors. The changing of business pattern of seller market to buyer market made a company has to adapt their need and changing behaviour. By having this base a company need to do market segmenting, targeting, and positioning with broadcast program in order to serve customers having different characteristics. This research aimed to find out how to apply segmenting, targeting dan positioning (STP) in Mitra 97.0 FM Radio of Batu City in determining the marketing strategy by considering STP. This research used also descriptive method drawing the execution of STP and the lack of the company in implementing STP. Form the analysis result done, Mitra 97.0 FM Radio of Batu City tried to serve the large market and divide its customers (listeners) in several segmenting variables. The applied marketing strategy was by developing products and promoting sales by personal selling, publishing, and advertising. In executing th...

This paper --a product of thc Public Scctor Managemcnt anzd Private Scctor Development Divisionl, Country Economics Dcpartrmcnt -is part ol'a largercffori in P'RE to: (1) asscss the divcstiture expericice to datc; (2) detcrmine tihc factors thial lcd to its succcss or failurc; and (3) suggest how thic World Banki and its borrowers ma) effectivel) use divestiturc as a public policy teol to cnhancc cconomic development. This paper is a revised version of a research proposal that the World Bankls Researclh Committec has approved for funding. Workl implentiiiilng thic proposed methodology is underway in Chile, Mexico, tlle U.K., and Malaysia.Copies of this paper are available free from the World Bank, 1818 H Street NW, Washinigton DC 2(433. Please contact Gloria Orraca-Tettch ,room N9-069, extension 37646 (31 pages). Thc economic rationale for divestiture rests on Galal suggests that to tease causalitv out of iwo propositions: that it will improve firms' the limited data thiat exists on this rclatively productive efficicncy and that it will reduice the receint phicnomlcnol, anal) sts compare datl on: budgetary burden that public enterprises inipose. -Th.' same cnierprise before and al'tcr But there hias been almost no empirical divestiture. analysis of what actually happens after divestiture, of which cntcrprises arc desiraiblc candio Divested and undivcstcd fimis in the samc dates, and under wOhat conditicns divcstiture sector and samc country. might improve a counlr)y's economic perf-ormance. * The performancc of tic divested ftrm and an explicit countcrfactual (the hypothetical perfor-Galal provides an analytical frameAork mance of the firm had it remained public). (partial equilibrium analysis) for assessing tiese basic argumcnts anid evalualting thic lessons of * The performance of divested firms in cxperiencc. competitivc and noncompetitive markefs in thc same country. To avoid the shiortcomings of the few studies that have becn done, Galal says thrce qluestions he Tle pcrformance of divested firms in the must bc asked: What are the changes in ecosame industr) but diffcrent countries. nomic efficienc) and Fiscal incidence, if any" What possible factors explain divestiture outcomes'? What is the causal linlk betwcen outcomes and their hypothetical detenninants'? Thc PRE W orking Pdper Scries discmllnalin thc findings of work under \,a\ in thi Rank's Policy, Research, and Extecmal Affairs Complex.An objectis \ of the sCries is to get thesc findings out quickl'..e cn if presentations are less than fully polishe(l. The findings, interpreaions. and conmlusions in thesc papers do not necessarily represent official Rank policy. Pf.du ,c d ls thie PRl L)o 55in ialtnr ('Ceitcr

According to Turkish Statistical Institute’s statistics and projections, the proportion of elderly people living in Turkey has an increasing trend over time and it is expected that Turkish population will be called old in the near future. Therefore, studies about elderly customers become more important since they will constitute a higher percentage of population when it is compared with the past. This study is designed to investigate behaviors about travel preferences of elderly travelers in Adana, Turkey, which will have a very old population in the future. For this purpose, we conduct a survey to examine travel preferences and priorities while choosing vacation routes, and barriers on traveling & issues related to quality of staff & service.

Background/Objectives: Accurate diagnosis of brain tumors is one of the most important challenges in neuro-oncology since tumor classification and volumetric segmentation inform treatment planning. Two-dimensional classification and three-dimensional segmentation deep learning models can augment radiological workflows, particularly if paired with explainable AI techniques to improve model interpretability. The objective of this research was to develop a web-based brain tumor segmentation and classification diagnosis platform. Methods: A diagnosis system was developed combining 2D tumor classification and 3D volumetric segmentation. Classification employed a fine-tuned MobileNetV2 model trained on a glioma, meningioma, pituitary tumor, and normal control dataset. Segmentation employed a SegResNet model trained on BraTS multi-channel MRI with synthetic no-tumor data. A meta-classifier MLP was used for binary tumor detection from volumetric features. Explainability was offered using XRAI maps for 2D predictions and Gaussian overlays for 3D visualizations. The platform was incorporated into a web interface for clinical use. Results: MobileNetV2 2D model recorded 98.09% classification accuracy for tumor classification. 3D SegResNet obtained Dice coefficients around 68-70% for tumor segmentations. The MLP-based tumor detection module recorded 100% detection accuracy. Explainability modules could identify the area of the tumor, and saliency and overlay maps were consistent with real pathological features in both 2D and 3D. Conclusions: Deep learning diagnosis system possesses improved brain tumor classification and segmentation with interpretable outcomes by utilizing XAI techniques. Deployment as a web tool and a user-friendly interface made it suitable for clinical usage in radiology workflows.

In recent years, one of the major challenges for financial institutions is the retention of their customers using new methodologies of reliable and profitable segmentation. In the field of banking, the approach of offering all of the services to all the existing customers at the same time does not always work. However, being aware of what to sell, when to sell and whom to sell makes a huge difference in the conversion rate of the customers responding to new services and buying new products. In this paper, we used RFM technique and various clustering algorithms applied to the real customer data of one of the largest private banks of Azerbaijan.

A 66-question online marketing survey of 2,800 football fans who had purchased tickets to a Division I, Power 5 (P5) university football game was conducted in order to understand the fan base and provide better services and targeted marketing. Principal Component Analysis was employed to combine responses from multiple questions about purchase behavior, on-site satisfaction, demographics, and other criteria. Subsequent market segmentation via cluster analysis indicated that 95% of the survey respondents could be categorized into one of five clusters. The identified fan perceptions and evaluations resulted in the P5 athletic department taking specific actions to improve targeted marketing activities and enhance game-day experiences, including improving the quality and diversity of food offerings, ensuring smoother ingress and egress, offering more precise ticket packages, and targeting groups through relevant marketing channels. The current research notes the importance of utilizing ...

This study delves into an in-depth analysis of the intricate factors that shape
service quality within tourism destinations situated in the Kashmir Valley. The
principal objective of this research is to meticulously scrutinize the diverse
elements that wield influence over service quality, with a particular emphasis on
the pivotal role played by infrastructure in the delivery of services. To achieve
this objective, the research encompasses an empirical verification process that
takes into account infrastructure-dependent, independent, and other pertinent
factors.
The nature and extent of these determinants are subjected to rigorous scrutiny at
an individual level across five distinct destinations, employing the robust Multiple
Linear Regression Model. The Service Quality Index, serving as the dependent
variable, amalgamates the aggregate value of indices across multiple dimensions.
Concurrently, factors influencing service quality are meticulously treated as
explanatory variables in the analytical framework.
The hypotheses put forth in this research are validated, affirming statistically
significant results. Intriguingly, the discerned significance predominantly aligns
with the factors reliant on infrastructure, rather than those operating
independently of it. Furthermore, the study reveals a lack of significant influence
exerted by industry-related factors on service quality within tourism destinations
in the Kashmir Valley.
In light of these findings, a strategic recommendation emerges for policymakers
to redirect their focus towards the enhancement of infrastructure-dependent
services as opposed to other service dimensions. The indispensability of
improving tourism infrastructure is underscored as a pivotal means to elevate
overall service quality within the context of tourism destinations in the Kashmir
Valley. This nuanced approach is integral to formulating effective policies geared
towards elevating the tourism experience and bolstering the region's
competitiveness in the global tourism landscape.
Key Words: Service Quality, Tourist Spots, Determinant Factors, and Policy
Perspectives

Berpetualang merupakan aktivitas yang menyenangkan, dimanapun kita bisa berpetualang termasuk di dunia maya. Namun kenapa kita harus mencoba berpetualangan di alam bebas. Alam bebas merupakan tempat bebas dari campur tangan manusia, dimana alamlah yang mendesain kondisi dan situasi yang ada, sehingga jarang manusia yang tinggal di sana karena berbahaya untuk dihuni oleh manusia pada umumnya. Pada umumnya manusia berkegiatan perkotaan dengan disuguhi oleh berbagai fasilitas yang mempermudah kegiatan manusia dalam beraktifitas. Dimana ada kendaraan untuk mempercepat perpindahan posisi, alat telekomunikasi untuk mempermudah berinteraksi satu sama lain, serta fasilitas lainnya untuk memenuhi kebutuhan hidup manusia. Berbeda dengan alam bebas, dimana fasilitas yang ada dikehidupan sehari-hari itu tidak bisa ditemui, adapun yang ada merupakan perlengkapan yang dibawa sekemampuan yang bisa kita bawa.

The authors present a methodology to evaluate and quantify the economic parameters (costs and benefits) attached to customer electricity consumption by analyzing the service provided by the different "pieces" of absorbed electricity. The first step of this methodology is to perform a process oriented market segmentation to identify segments according to their flexibility potential. After that, a procedure based on comprehensive simulations to identify and quantify the actual demand that can be managed in the short term is presented and, finally, the required economic analysis is performed. The methodology, which is demonstrated with some applications to the commercial sector, not only helps the customers to integrate in flexible distribution systems but also offers the necessary economical parameters for them to integrate in electricity markets.

The objective of the study vas to explore the appropriateness of several statistical techniques in developing predictive models of consujiaers' long distance telephone expenditux-e based on the analysis of socioeconomic and demographic characteristics. Specifically, the paper examines the relative efficacy of stepwise multiple regression, monotonic A.ID (Automatic Interaction Detector) and free AID in analyzing large scale data. Most consumer behavior research to date has been ad hoc, fragmentary, and exploratory. Only irecently have large corporations begun to generate continoxis and systematic infonnation about the market place as part of their marketing information systems. The Bell System Companies provide comm\ini cation services in the hB continentaJ. states and the District of Columbia to lOU million telephones, 83/^of the total telephones in the United States. The need to understand this er-onaous mai-ket is self-evident, not only from a traditional marketing view but also from the social and economic considerations inherent in the laarageTnent of a regulated utility. To help meet this need, a latrge scale Market Research Information System (MRIS) has been established, consisting oi a national longitudinal panel of some 60,000 customers representing both the business and residence markets.

Though graph cut based segmentation is a widely-used technique, it is known that segmentation of a thin, elongated structure is challenging due to the "shrinking problem". On the other hand, many segmentation targets in medical image analysis have such thin structures. Therefore, the conventional graph cut method is not suitable to be applied to them. In this study, we developed a graph cut segmentation method with novel Riemannian metrics. The Riemannian metrics are determined from the given "initial contour," so that any level-set surface of the distance transformation of the contour has the same surface area in the Riemannian space. This will ensure that any shape similar to the initial contour will not be affected by the shrinking problem. The method was evaluated with clinical CT datasets and showed a fair result in segmenting vertebral bones.

The involvement construct has been extensively applied in consumer behavior research and used to profile consumers and explain their consumption behavior. More recently, in the context of tourism, it has been used to explain tourists’ purchase behavior (Josiam, Kinley & Kim, 2005; Smith & Pan, 2009), information search (Gursoy & McCleary, 2004), preferences (Cai, Feng, & Breiter, 2004), destination experiences (Letho, O’Leary & Morrison, 2004), and place attachment (Gross & Brown, 2006). Several scales have already been tested based on Laurent and Kapferer’s (1985) and/or Zaichkovsky’s (1985) seminal works, such the case of Gursoy and Gavcar’s (2003) scale, which is applied to tourism. However, previous research has not yet examined tourist involvement in the context of rural destinations, despite a demanding market for rural tourism is growing (Lane, 2009). Against this background, this study focuses on consumer involvement theory and aims at validating Gursoy and Gavcar’s (2003) s...

The subject matter: this article analyzes and designs a system based on deep learning to strip the human Skull into three views. The goal was to design a system that separates the Skull, keeps the brain based on MRI images, and allows the three sections to work in a 3D system. The tasks to be solved Skull stripping in three axes (axial, sagittal, and coronal) together to obtain a 3D image and test the system on other data that the system has not been trained on to ensure its efficiency in isolating the human Skull The methods used are: The proposed system used two stages for the work: the first is image processing based on deep learning technology by relying on the CLAHE filter to do equalization of the images, i.e., work on lightening the dark areas and darkening the light areas and using normalization. Moreover, the use of deep learning technology on a pre-trained model (EfficientNet-B0) for the training process and the use of hold-out methods to divide the data into training, testing, and evaluation. Moreover, to evaluate the work efficiency using the scale (dice coefficient) and the dataset using NFBS for training and testing and IBSR for only testing, the Results were obtained: The results obtained for the NFBS dataset from the training are (accuracy =98% and F1-score=98.4%) and from the test are (dice-score = 99.9%), and the results of the external test data set IBSR are (dice-score = 99.9%). Conclusions: The process of isolating the Skull is an essential step in diagnosing diseases of the human brain, and the image processing process is an essential step to prepare the data that will be trained on, as well as the strategy for transforming the efficient-b0 model's training into the structure of the u-net model in terms of in-depth training on a large variety of languages with good accuracy and testing processes. External data is used to assess whether a system is operating efficiently.

ABSTRACTThe segmentation of individual instances of mitochondria from imaging datasets is informative, yet time-consuming to do by hand, sparking interest in developing automated algorithms using deep neural networks. Existing solutions for various segmentation tasks are largely optimized for one of two types of biomedical imaging: high resolution three-dimensional (whole neuron segmentation in volumetric electron microscopy datasets) or two-dimensional low resolution (whole cell segmentation of light microscopy images). The former requires consistently predictable boundaries to segment large structures, while the latter is boundary invariant but struggles with segmentation of large 3D objects without downscaling. Mitochondria in whole cell 3D EM datasets often occupy the challenging middle ground: large with ambiguous borders, limiting accuracy with existing tools. To rectify this, we have developedskeletonorientedobject segmentation (SKOOTS); a new segmentation approach which effi...

Brain tumor segmentation from Magnetic Resonance Images (MRI) is considered a big challenge due to the complexity of brain tumor tissues, and segmenting these tissues from the healthy tissues is an even more tedious challenge when manual segmentation is undertaken by radiologists. In this paper, we have presented an experimental approach to emphasize the impact and effectiveness of deep learning elements like optimizers and loss functions towards a deep learning optimal solution for brain tumor segmentation. We evaluated our performance results on the most popular brain tumor datasets (MICCAI BraTS 2020 and RSNA-ASNR-MICCAI BraTS 2021). Furthermore, a new Bridged U-Net-ASPP-EVO was introduced that exploits Atrous Spatial Pyramid Pooling to enhance capturing multi-scale information to help in segmenting different tumor sizes, Evolving Normalization layers, squeeze and excitation residual blocks, and the max-average pooling for down sampling. Two variants of this architecture were con...

In this paper, a novel K-means clustering algorithm is proposed. Before running the traditional Kmeans, the cluster centers should be randomly selected, which would influence the time cost and accuracy. To solve this problem, we utilize density distribution analysis in the traditional K-means. For a reasonable cluster, it should have a dense inside structure which means the points in the same cluster should tightly surround the center, while separated away from other cluster canters. Based on this assumption, two quantities are firstly introduced: the local density of cluster center ρi and its desperation degree δi, then some reasonable cluster centers candidates are selected from the original data. We performed our algorithm on three synthetic data and a real bank business data to evaluate its accuracy and efficiency. Comparing with Traditional K-means and K-means++, the results demonstrated that the improved method performs better.

This research identifies market segments among university students based on media promotion usage. It examines the impact of media promotions on the choice of programs and institutions of open and distance university institutions. This study used a quantitative methodology, and the population studied consisted of all currently enrolled Universitas Terbuka students throughout Indonesia, with a total sample of 2,250 people. In this research, market segmentation has been carried out using the cluster method, which includes demographic, geographic, psychographic, and behavioral segments. The demographic segment that is assessed age and gender of students, recent graduates, and income; The geographic segment is mapped to the origin of the UT regional offices; the psychographic segment includes reasons for studying and choosing UT; and the behavioral segment from which information is first and most effective. This research implies that the results can be used as a reference in supporting ...

This paper shows how the welfare effects of third-degree price discrimination may be decomposed into two effects: a misallocation effect and an output effect. It also presents a geometrical analysis which shows how the welfare properties of third-degree price discrimination must be assessed using nonlinear demands, and hence how linear demands are not suitable for the analysis.

This article discusses the viability of targeting heavy spenders on non-gaming products and services in gaming travel marketing. A sample of visitors to two commercial casinos [in the USA](sampled between 28 May and 9 September 2000) was divided into ...

This study delves into the property submarket in Kuala Lumpur and Selangor, Malaysia. The submarket is anticipated to be simple, uniform, and dense, making it highly influenced by neighbouring properties. However, traditional data-driven methods that overlook spatial contiguity disregard this density condition. To tackle this problem, the study investigates spatially constrained data-driven methods utilizing Principal Component Analysis (PCA) and cluster analysis. The findings reveal that spatially constrained methods outperform traditional methods by minimizing errors and enhancing model fit. Specifically, the two-step cluster method and k-means cluster method reduce errors by 6.96% and 7.22%, respectively, but at the cost of model fit by 11.23% and 13.94%. Conversely, the spatial k-means and spatial agglomerative hierarchical cluster methods reduce errors by 8.68% and 8.17%, respectively, while improving model fit by 7.1% and 6.35%. Hence, the study concludes that spatially constrained data-driven methods are more effective in differentiating commercial property submarkets than traditional methods.

The World Bank estimates that closing the gender gap in employment and entrepreneurship could increase the global GDP by more than 20%. However, despite decades of government initiatives, legislation and equal opportunity policies, the gender gaps in entrepreneurship, STEM, ICT and related sectors still prevail. Current research confirms women's underrepresentation, along with the gender gaps in skills which will be crucial for the future of work, like AI, Cybersecurity and Big Data. The current Global Gender Gap Report and Index (WEF, 2025) estimates that the overall global gender gap could be closed in 123 years, if we continue at this pace! This paper argues that gender devaluation reproduces social stereotypes and consequently the gendered skills shortages. Empowering women and increasing the talent pool requires engendering technology, namely inspiring girls and women into technology: i.e. eliminating stereotypes and raising the profile of female role models and mentors. This entails women's agency and economic empowerment. We cannot afford to wait 123 years to reach full parity. The "Care Burden Impact", highlighted in the Global Gender Gap Report, confirms that the surge in caregiving responsibilities is limiting women's employability, indicating the urgent need for inclusive practices in addition to a more just care economy, equitable care systems and policies.

When investigating a large or damaging seismic event in a mine, it is possible to be in the situation where either a conventional source mechanism inversion technique is not applicable due to poor data or the interpretation of the inverted source mechanism in terms of a planar slip model does not appear adequate for the observed damage or geological/mining settings. In such cases we use an approach that could be called 'testing of source processes'. It comprises two modifications: (A) modelling of the mechanism (single force or moment tensor) of a hypothesized source process and its comparison with the source mechanism inverted from seismic data, (B) modelling of seismic signals from the hypothesized source mechanism(s) and their comparison with the recorded waveforms. The mechanisms of non-conventional source processes (e.g. rock fall, pillar burst, strain burst) can be rigorously modelled using either the low-frequency part of seismic radiation described by a single force ...

Background: There is a fluctuating trend related to the number of patient visits at Nur Hidayah Hospital, Bantul, so it is necessary to formulate the right Segmentation, Targeting, and Positioning (STP) in order to increase inpatient and outpatient visits and achieve standard inpatient service indicators. The purpose of this study is to analyze the marketing strategy of Nur Hidayah Hospital based on STP. Method: This study follows a descriptive qualitative design. The key informants in this study were the general director and the marketing manager of the hospital, and the triangulation informants in this study were medical officers and patients. Results: The results revealed that the segmenting was based on demographics with females or housewives with secondary education levels or lower as the highest number of service users. Based on the geographical characteristics, a significant number of service users were those living in Ring 1, an area within a radius of 0-10 km from the hospi...

This article discusses the viability of targeting heavy spenders on non-gaming products and services in gaming travel marketing. A sample of visitors to two commercial casinos [in the USA](sampled between 28 May and 9 September 2000) was divided into ...

We determine market segments by clustering households on the basis of their average choice elasticities across purchases and brands w.r.t. price, sales promotion and brand loyalty. The cluster analysis technique used is a maximum likelihood method which allows varying size and orientation and assumes constant volume. Elasticities originate from choice models with alternatively linear and nonlinear utility functions. Choice models are estimated on the basis of household scanner data. Segments are interpreted by means of multiple discriminant analysis and multinomial logit models whose predictors are elasticities of predictors and external variables (i.e. number of purchases, number of brands bought, income and household size), respectively.

We determine market segments by clustering households on the basis of their average choice elasticities across purchases and brands w.r.t. price, sales promotion and brand loyalty. The cluster analysis technique used is a maximum likelihood method which allows varying size and orientation and assumes constant volume. Elasticities originate from choice models with alternatively linear and nonlinear utility functions. Choice models are estimated on the basis of household scanner data. Segments are interpreted by means of multiple discriminant analysis and multinomial logit models whose predictors are elasticities of predictors and external variables (i.e. number of purchases, number of brands bought, income and household size), respectively.

Limits of Arbitrage" theories hypothesize that the marginal investor in a particular asset market is a specialized arbitrageur rather than a diversified representative investor. We examine the mortgagebacked securities (MBS) market in this light. We show that the risk of homeowner prepayment, which is a wash in the aggregate, is priced in the MBS market. The covariance of prepayment risk with aggregate wealth implies the wrong sign to match the observed prices of prepayment risk. The price of risk is better explained by a kernel based on MBS-market-wide specific risk. This finding is consistent with the specialized arbitrageur hypothesis.

This paper argues that a shift is occurring in the labor market structure leading to an increase in the use of social networks based on the criteria that were originally the locus of labor market segmentation in low income jobs: race, sex and ethnicity, but also age, disability and sexual orientation. It thus calls into question the presumption of the earlier literature on labor market segmentation that as one moved up the wage hierarchy, jobs were increasingly allocated through formal institutional structures on the basis of objective credentials, and that the adverse labor market outcomes of minority groups in low wage jobs were connected to excessive reliance upon social networks in the labor market.

This community service aims: to be able to help the management of the Sirah Pamali Spring tourist attraction, Winduaji village, Paguyangan District, Brebes Regency understand the potential of tourism human resources and understand consumer psychology in an effort to segment the Sirah Pamali tourism object market. This community service uses a subject of 21 participants from various elements supporting Sirah Pamali tourism. The material for community service is to introduce and practice various things, including: (1) reorienting tourism during the pandemic and post-pandemic period; (2) recognize the concept of market segmentation; (3) identify consumer needs for tourism market mapping and marketing design; and (4) implementation of consumer psychology in an effort to promote tourism in Sirah Pamali Springs. Implementation of the training, with lectures, discussions, and simulation-practice methods accompanied by feedback. In conclusion, the Training of Human Resources Development for...

The use of AI-powered personalization in real-money gaming has raised significant ethical and regulatory concerns in recent years. These systems are usually designed to maximize user engagement with the platform, which leads to higher monetization, but this sometimes comes at the cost of opaque and potentially discriminatory targeting systems, which risk exploiting user behavior, particularly among the vulnerable population. This study aims to address these issues by developing a regulatory-aligned framework that integrates ethical constraints such as fairness, transparency, and harm mitigation directly into the design of personalization algorithms. Drawing on secondary qualitative sources such as regulatory frameworks, peer-reviewed literature, and documented platform practices, this study analyzes current standards and gaps in industry practice. These insights inform the creation of the Responsible Personalization Framework (RPF), which operationalizes regulatory principles through concrete design patterns. The findings reveal that widely adopted personalization strategies often contradict responsible AI principles. However, the proposed framework, featuring mechanisms like Harm-Aware Personalization and the Offer Parity Rule, offers actionable, regulation-compliant solutions for ethical personalization. Overall, the study demonstrates that embedding ethical and regulatory safeguards at the design stage, instead of post hoc reactive enforcement, enables the development of safer, fairer, and more responsible AI systems in the context of real-money gaming.

O turismo tem se mostrado uma alternativa viável para a manutenção do patrimônio natural. Entretanto, em alguns ecossistemas, tais como os ambientes subterrâneos, ainda são necessários muitos estudos para tornar esta atividade pouco impactante. O objetivo do presente trabalho foi avaliar as comunidades biológicas (riqueza, diversidade, equitabilidade, similaridade e complexidade ecológica), e as alterações que podem vir a ocorrem nas condições ambientais (temperatura e umidade relativa) advindas do turismo no interior de cavidades subterrâneas artificiais. A iluminação elétrica do tipo incandescente determinou alterações na temperatura e umidade relativa de minas turísticas. No entanto, as comunidades não apresentaram mudanças significativas na estrutura, uma vez que aquelas presentes em cavidades turísticas se mostram muito semelhantes àquelas presentes em minas não turísticas. Embora estes estudos ainda sejam incipientes no país, os mesmos já demonstram a urgente necessidade de criação de propostas de uso turístico que causem o menor impacto possível aos ambientes subterrâneos quando da instalação do uso turístico.

This paper empirically studies financial benefits of equity market integration at the firm level in emerging economies. It explores the unique setting of public firms cross-listing on a new domestic stock exchange, as a means to enhance their access to capital and overcome market frictions in previously fragmented equity markets. Following the opening of India’s National Stock Exchange in the early 1990s, dual-listed firms increased investment relatively more than their peers which remained listed on the country’s primary market (Bombay Stock Exchange), and this was more pronounced in firms considered financially constrained ex-ante. These results can be explained by larger equity offerings and reduced information asymmetries in raising new capital, subsequently to cross-listing. However, valuations of dual-listed firms which failed to sustain a more liquid trading environment for their shareholders returned to pre-crosslisting levels over time. This evidence suggests that financial...

Unlocking the value of raw data requires transforming it into knowledge and information that drives decision-making. Algorithms for Machine Learning (ML) are capable of analyzing big datasets and delivering accurate predictions. Using machine learning, market segmentation, customer lifetime value, and marketing approaches have been used. This article explores machine learning approaches for marketing, including Support Vector Machines, Genetic Algorithms, Deep Learning, and K-Means. It is rare for ML to be used to forecast when a person will purchase a product or a basket of goods.

The value of raw data is unlocked by converting it into information and knowledge that drives decision-making. Machine Learning (ML) algorithms are capable of analysing large datasets and making accurate predictions. Market segmentation, client lifetime value, and marketing techniques have all made use of machine learning. This article examines marketing machine learning techniques such as Support Vector Machines, Genetic Algorithms, Deep Learning, and K-Means. ML is used to analyse consumer behaviour, propose items, and make other customer choices about whether or not to purchase a product or service, but it is seldom used to predict when a person will buy a product or a basket of products. In this paper, the survival models Kernel SVM, DeepSurv, Survival Random Forest, and MTLR are examined to predict tine-purchase individual decisions. Gender, Income, Location, PurchaseHistory, OnlineBehavior, Interests, PromotionsDiscounts and CustomerExperience all have an influence on purchasi...

GLM|LIC Synthesis Paper No. 6 | August 2017 What Constrains the Demand for Labour in Firms in Sub-Saharan Africa? Some Evidence from Ghana Employment in Ghana’s manufacturing sector remained constant as a share of total employment from 1962 to 2014 at just over 10 per cent. However the share of employment in small scale enterprises, those employing less than 10, doubled in urban areas from 33 to 64 percent of the total. Such enterprises have much lower levels of labour productivity than larger ones. In this paper the possible reasons for this pattern of job expansion in the lower productivity sector are examined by combining census and survey data. It is shown that large firms use a much more capital intensive technology than smaller ones, face lower capital costs and pay higher wages. Possible reasons for these patterns of factor demand and factor prices are examined. Hypotheses that explain higher wages in larger firms include efficiency wages, rent capture, market frictions in se...

Resumen La permanencia de las organizaciones, entre ellas las empresas, requiere del mantenimiento y formación de un conjunto de capacidades que conjuguen la eficiencia y la innovación. Lo anterior se acentúa cuando en el entorno se presentan acontecimientos que cambian de modo radical las condiciones en las que se desempeñan las organizaciones. Este es el caso de las crisis económicas, por desastre y de otra índole, a las que se enfrentan las organizaciones, en particular, y la sociedad en general. Al respecto, el artículo tiene la finalidad de identificar las estrategias instrumentadas por los restaurantes en diferentes contextos de crisis, así como el tipo de capacidades involucradas, tomando como base la distinción entre capacidades dinámicas y capacidades ordinarias. Para ello, se recurre a la revisión de literatura como propuesta metodológica y se selecciona una muestra de 271 artículos y actas/ponencias en congresos. Se observa que la teoría de capacidades dinámicas es pertinente para el estudio del desenvolvimiento de la industria

Konaklama işletmeleri verimliliklerini artırmak için, birbirinden farklı ihtiyaç, istek ve tercihleri olan potansiyel müşterilerini belli özelliklere göre bölümlere ayırmakta ve bu bölümlerden bazılarını hedef pazar olarak seçmektedir. Dünya ticaretinde yaşanan hızlı gelişmeler nedeniyle iş seyahatlerinin artması, özellikle şehir otelleri için iş insanları pazar bölümünü oldukça önemli bir hale getirmiştir. Bundan dolayı bu araştırmada, iş insanlarının konaklama tercihlerini etkileyen faktörlerin belirlenmesi amaçlanmıştır. Verilerin toplanmasında anket tekniği ve kota örneklemesi kullanılmıştır. Anket, Mersin ve Adana şehir merkezinde faaliyet gösteren dört ve beş yıldızlı toplam 10 otel işletmesinde, 2011 yılı Nisan-Aralık ayları arasında 600 iş insanına uygulanmıştır. İş insanlarının konaklama tercihlerinde etkili olan aktivite olanakları, otel imajı, ulaşım kolaylığı, temizlik etkeni, çalışma ortamı ve ilgi ve hız adlarında altı faktör tespit edilmiştir. Bulgulara bağlı olarak konaklama işletmeleri, kamu kurumları ve yeni araştırmacılar için çeşitli öneriler geliştirilmiştir.

Impulsive buying is an unexpected or unplanned buying or purchase. The principal intention of this research was to consider the influence of different intrinsic factors on impulsive buying tendencies. Hence, internal factors focus on the individual's internal cues and individualities. Such factors involve the consumer's personality traits. Moreover, the following were taken as internal factors for this study: excitement factors, esteem factors, new product knowledge and hedonistic factors. After engaging this quantitative study, a questionnaire was utilized to gather data. Consequently, the information was composed from one hundred sixty-two college students of Surigao del Sur State University. It was found out that the respondents were reminded type of impulsive buyers who mind choosing what to acquire by looking at first the products in the store. With regards to their degree of impulsive buying intention, they manage to buy impulsively according to how they feel at an instant, but they certainly not consider of buying a new product even if they haven't heard it yet. The findings also exposed that intrinsic factors significantly and most of the time influence the Impulsive Buying Behavior. The Esteem Factor was sought to influence the respondents' impulsive buying behavior all the time. Generally, results have been discovered to be substantial and possibly will be adopted and executed for marketing strategy making by numerous stakeholders in the field of consumer psychology and consumer behavior to figure out the influence of internal factors on impulsive buying behavior.

In the earlier paper, we analyzed a possibility of CDM domino, where CDM (Clean Development Mechanism) is a flexibility mechanism adopted in the Kyoto protocol (KP) for the international scheme to prevent climate change due to emission of green house gases (GHG), and domino means adoption of one CDM project induces other CDM projects. In this paper, we attempt to analyze the opposite effect of project based mechanisms including CDM, i.e. the negative impact of adoption of one project upon other potential projects. This possibility has an important implication on the technological development for the prevention of climate change, as the early adoption of a technology receives an unduly special position so that newly developed technology has relatively fewer chances of a success. Even though people disagree over many issues, there seem to be widespread agreement that technological breakthrough is a key element for the long run success of international climate policy. Thus the evaluation of the effect of mechanisms on the technology development to overcome current reliance on carbon intensive technology is important, especially in the ongoing negotiation toward new schemes to be instituted for the period following the period covered by (KP).