1000 and counting :-)

And the pageviews for this blog reach four digit mark !!

AMRP presentation

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AMRP report

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Interesting Read - "Appily ever after: A smartphone shrink"

A proliferation of psychology smartphone apps - with names like BreakkUp, iStress and myinstantCOACH - purports to help us live happier, less anxious lives. As Mark McGonigle, a therapist in Kansas City, Mo., who invented the app Fix a Fight, puts it: "Electronic devices don't have to drive us apart. They can bring us together." Which sounds so good. A few bucks and a lot of squinting into my phone: that certainly beats a $300-an-hour psychiatrist, right?

Read the full article here: http://gadgets.ndtv.com/apps/news/appily-ever-after-a-smartphone-shrink-351299
Funny stuff, this !!

Cluster Analysis - What it is?

Cluster analysis is a class of statistical techniques that can be applied to data that exhibit “natural” groupings. Cluster analysis sorts through the raw data and groups them into clusters. A cluster is a group of relatively homogeneous cases or observations. Objects in a cluster are similar to each other. They are also dissimilar to objects outside the cluster, particularly objects in other clusters.

In marketing, cluster analysis is used for

·         Segmenting the market and determining target markets

·         Product Positioning and New Product Development

·         Selecting test markets

Examples

The diagram below illustrates the results of a survey that studied drinkers’ perceptions of spirits (alcohol). Each point represents the results from one respondent. The research indicates there are four clusters in this market. The axes represent two traits of the market. In more complex cluster analyses you may have more than that number.

Another example is the vacation travel market. Recent research has identified three clusters or market segments. They are: 1) The demanders - they want exceptional service and expect to be pampered; 2) The escapists - they want to get away and just relax; 3) The educationalist - they want to see new things, go to museums, go on a safari, or experience new cultures.

Cluster analysis, like factor analysis and multi-dimensional scaling, is an interdependence technique: it makes no distinction between dependent and independent variables. The entire set of interdependent relationships is examined. It is similar to multi-dimensional scaling in that both examine inter-object similarity by examining the complete set of interdependent relationships. The difference is that multi-dimensional scaling identifies underlying dimensions, while cluster analysis identifies clusters. Cluster analysis is the obverse of factor analysis. Whereas factor analysis reduces the number of variables by grouping them into a smaller set of factors, cluster analysis reduces the number of observations or cases by grouping them into a smaller set of clusters.

Apps dominate smartphone usage, survey finds

According to figures collated by analytics firm Flurry, over the past five years smartphone usage has become increasingly tilted towards heavy app use.

Read more at http://www.trustedreviews.com/news/apps-dominate-smartphone-usage-survey-finds

Relative Importance of purchase determinants

Based on the responses received, the relative importance of purchase determinants for apps for different categories was assessed, and charts were created in MS Excel for ease of presentation.
(The charts represent average importance of various factors on a five point scale, 5 representing highest importance)

Questionnaire Snapshot

A snapshot of the questionnaire developed to assess the relative importance of purchase determinants of Smartphone apps, and to cluster the users of apps.

A broad Classification of Smartphone Apps (to study purchase determinants)

Now that we have established the validity of extended TAM for acceptance of Smartphone apps, let us examine the key determinants in deciding the purchase of Smartphone Apps. Because customers may have different consideration factors in deciding the purchase depending on the App type, we first classified Apps into 4 categories:

Productivity Entertainment, Information, and Networking

Let's dive deeper !!

The scope of this research has been extended to dive deeper into the world of Smartphone apps. The objectives of the study are three-fold:

• To propose an integrated theoretical framework of Smartphone Applications’ acceptance and intention to use based mainly on the Technology Acceptance Model (TAM). 
• To identify the key determinants in deciding purchase of Smartphone applications and establish their order of importance.
• To analyze the usage pattern of Smartphone apps and to classify the users into different groups based on their usage of apps and factors they consider during purchase of apps. 

AMRP Interim Report

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AMRP Interim Presentation

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Literature Review - Research Paper Summary (Contd.)

PAPER TITLE : Understanding Customers' Acceptance of Online Purchasing

AUTHOR : Donald L. Amoroso, D. Scott Hunsinger

SUMMARY
This paper examines previous Technology Acceptance Model (TAM)-related studies in order to provide an expanded model that explains consumers’ acceptance of online purchasing. The model provides extensions to the original TAM by including constructs such as social influence and voluntariness; it also examines the impact of external variables including trust, privacy, risk, and e-loyalty.
The findings suggest that the expanded model serves as a very good predictor of consumers’ online purchasing behaviors. The linear regression model shows a respectable amount of variance explained for Behavioral Intention. Not only are the traditional TAM variables important in predicting behavioral intention, but social influence, perceived behavioral control, and e-loyalty are all significant constructs. It seems that the model is quite robust in predicting Behavioral Intention. The study also discovered that trust, a construct not included in the original TAM, plays an important role in influencing consumers’ attitudes toward purchasing.

Literature Review - Research Paper Summary (Contd.)

PAPER TITLE : Why do people play on-line games? An extended TAM with social influences and flow experience

AUTHOR : Chin-Lung Hsu and  Hsi-Peng Lu

SUMMARY
This study applies the technology acceptance model (TAM) that incorporates social influences and flow experience as belief related constructs to predict users’ acceptance of on-line games. It contributes to a theoretical understanding of the factors that promote entertainment-oriented IT usage such as on-line games. Entertainment-oriented IT differs from task oriented IT in terms of reason for use. Task-oriented IT usage is concerned with improving organization productivity. Therefore, TAM stresses the importance of perceived usefulness and perceived ease-of-use as key determinants. However, in the context of entertainment-oriented IT, this study demonstrates that the importance of individual intentions tends to need other variables: social norms and flow experience. Furthermore, this dominance is strong, and these variables explain much of the variance in entertainment technology usage. Overall, the results reveal that social norms, attitude, and flow experience explain about 80% of game playing.

Literature Review - Research Paper Summary (Contd.)

PAPER TITLE : A Conceptual Framework and Propositions for the Acceptance of Mobile Services

AUTHOR : Sally Rao and Indrit Troshani

SUMMARY
The research paper is explores, analyzes and critically assesses the use of existing acceptance theories in the light of the evolving and ubiquitous mobile services and their underlying technologies. Personalisation, ubiquity and location specificity of mobile services make their adoption somewhat different from other Information and Communication Technology (ICT) services. Further, mobile technologies and the associated services integrate both the business and social domains of the user’s life.
The paper extends the existing models to propose an integrated and eclectic conceptual
framework which attempts to explain adoption behaviour of users of mobile services.

Literature Review - Research Paper Summary (Contd.)

PAPER TITLE : A Pilot Study to Analyze the Effects of User Experience
and Device Characteristics on the Customer Satisfaction of Smartphone Users

AUTHOR : Bong-Won Park and Kun Chang Lee

SUMMARY
Recently, people are beginning to use the smartphone and want to use it smartly. At this time, satisfied customers communicate their positive experiences to others. Therefore, to expand smartphone markets, a company should try to satisfy existing smartphone customers. The study analyzes the factors that affect customer satisfaction respective of user experience and device characteristics.
Smartphone stress is categorized into three components: device-related stress, data/application
stress, and new-learning stress. Device-related stress means that the stress occurs when
the smartphone is not working or is down. Data/application stress means that the stress
occurs when the stored data crashes or the application is not working. New-learning
stress means that as new applications and features are included, users have to learn new
applications and features. However, smartphone stress is not an important factor
regarding user satisfaction because early adopters are tech-savvy and find it less
difficult to use new devices than average persons. Therefore, such users do not get
stressed from using smartphones.
Instant connectivity, which connects users anywhere anytime to the Internet, is an important factor that impacts smartphone users’ satisfaction. Many users are familiar with the Internet, and want to use the Internet anytime anywhere and free of charge. This need is fulfilled through smartphones that are embedded with Wi-Fi functionality.

Literature Review - Research Paper Summary

PAPER TITLE : Extending the Technology Acceptance Model to Account for Social Influence:
Theoretical Bases and Empirical Validation

AUTHOR : Yogesh Malhotra, Dennis F. Galletta

SUMMARY
The Technology Acceptance Model (TAM) represents an important theoretical contribution toward understanding IS usage and IS acceptance behaviors. However, TAM is incomplete in one important respect: it doesn't account for social influence in the adoption and utilization of new information systems. The findings of this study suggest that social influences play an important role in determining the acceptance and
usage behavior of new adopters of new information technologies. When social influences generate a feeling of compliance, they seem to have a negative influence on the users' attitude toward use of the new information system. However, when social influences generate a feeling of internalization and identification on the part of the user, they have a positive influence on the attitude toward the acceptance and use of the new system. The findings also suggest that internalization of the induced behavior by the adopters of new information system plays a stronger role in shaping acceptance and usage behavior than perceived usefulness (PU). Hence the consideration of social influences and how they affect the commitment of the user toward use of the information system seems important for understanding, explaining and predicting system usage and
acceptance behavior.

Unified Theory of Acceptance and Use of Technology (UTAUT)

The UTAUT aims to explain user intentions to use an IS and subsequent usage behavior. The theory holds that four key constructs (performance expectancy, effort expectancy, social influence, and facilitating conditions) are direct determinants of usage intention and behaviour (Venkatesh et. al., 2003). Gender, age, experience, and voluntariness of use are posited to mediate the impact of the four key constructs on usage intention and behavior (Venkatesh et. al., 2003). The theory was developed through a review and consolidation of the constructs of eight models that earlier research had employed to explain IS usage behaviour (theory of reasoned action, technology acceptance model, motivational model, theory of planned behavior, a combined theory of planned behavior/technology acceptance model, model of PC utilization, innovation diffusion theory, and social cognitive theory). Subsequent validation of UTAUT in a longitudinal study found it to account for 70% of the variance in usage intention (Venkatesh et. al., 2003).

Technology Acceptance Model (TAM)

TAM is an adaptation of the Theory of Reasoned Action (TRA) to the field of IS. TAM posits that perceived usefulness and perceived ease of use determine an individual's intention to use a system with intention to use serving as a mediator of actual system use. Perceived usefulness is also seen as being directly impacted by perceived ease of use. Researchers have simplified TAM by removing the attitude construct found in TRA from the current specification (Venkatesh et. al., 2003). Attempts to extend TAM have generally taken one of three approaches: by introducing factors from related models, by introducing additional or alternative belief factors, and by examining antecedents and moderators of perceived usefulness and perceived ease of use (Wixom and Todd, 2005).

TRA and TAM, both of which have strong behavioural elements, assume that when someone forms an intention to act, that they will be free to act without limitation. In practice constraints such as limited ability, time, environmental or organisational limits, and unconscious habits will limit the freedom to act

Smartphone users around the world

Infographic by- GO-Gulf.com Web Design Company