User-generated Destination Image through Weblogs: A Comparison of Pre- and Post-visit Images

Posted on 06/03/2011 by Jean Eric PELET

Author(s) : Dev Jani et Yeong-Hyeon Hwang

Introduction : On constate une augmentation forte du choix de destination de voyage par internet, par l’intermédiaire de plateformes-internet dédiées. Mais peu de travaux réaliser sur l’influence des blogs et forums internet(capture d’image de manière holistique). L’influence de l’internet sur la destination touristique n’est pas encore prouvée (de par sa grandeur et sa diversité). Blankson et Kalafatis (2004) il y a un manque de recherche sur la manière dont les consommateurs se forment une image de marque. Gover (2009) Remarque un manque d’études sur le processus de formation d’images. Alors que la plus part des études porte sur le comportement des touristes.

Hypothèse :

Quelles sont les éléments communs entre Zanzibar comme destination touristique et perçue par un communiqué au touristes de Zanzibar sur des blogs ou forums ?

Il y a t’il une différence entre l’image que ce font les touristes qui planifient de visiter et se qui l’on déjà visités ?

Résultat : Tasci et Al (2007), définissent l’image du lieu de destination comme comportant 3 composants :

– Cognitif (réflexion)

– Affectif (sentiments)

– Conatif (intension de comportement)

Tous sont liés à la définition de l’attitude.

Conclusion :

Visualisation and Instructional Design

Posted on 05/20/2011 by Jean Eric PELET

Author(s) : John Sweller

1. Topic

This article is about the limited capacity of the working memory and how to optimize its use. After describing the information structure, it develops the human cognitive architecture. Working memory, long-term memory, schemas and automation are the elements of the human cognitive architecture relevant to visually based instructional design. This leads to the instructional effects of the cognitive load theory. At last the paper explores the interaction of information and cognitive structures and how to optimize visually based instructional design through concepts like the split-attention effect, the modality effect, the redundancy effect, the element interactivity effect and the imagination effect.

2. Reference

1.   Bartlett, F. (1932). Remembering: A study in experimental and social psychology. London:Cambridge University Press.
2.   Chase, W. G. & Simon, H. A. (1973). Perception in chess. Cognitive Psychology, 4, 55 – 81.
3.   Cooper, G., Tindall-Ford, S., Chandler, P. & Sweller, J. (2001). Learning by imagining. Journal of Experimental Psychology: Applied, 7, 68-82.
4.   De Groot, A. (1965). Thought and choice in chess. The Hague, Netherlands: Mouton. (Originalwork published 1946).
5.   Larkin, J., McDermott, J., Simon, D., & Simon, H. (1980). Models of competence in solving physics problems. Cognitive Science, 4, 317-348.
6.   Marcus, N., Cooper, M., & Sweller, J.    (1996). Understanding instructions. Journal of Educational Psychology, 88, 49-63.
7.   Miller, G.A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81-97.
8.   Peterson, L. & Peterson, M. (1959). Short-term retention of individual verbal items. Journal of Experimental Psychology, 58, 193-198.
9.   Piaget, J. (1928). Judgement and reasoning in the child. New York: Harcourt.
10.   Schneider, W., & Shiffrin, R. (1977). Controlled and automatic human information processing: I. Detection, search and attention. Psychological Review, 84, 1-66.
11.   Sweller, J. (1994). Cognitive load theory, learning difficulty and instructional design. Learning and Instruction, 4, 295-312.

3. Literature review

The author uses numerous references to the work of other academic writers and their findings covering a long period as well as his own past work. He also often refers to the same authors. He refers to: Sweller (1994) , Miller(1956), Peterson and Peterson (1959), De Groot’s (1965), Piaget (1928), Bartlett (1932), Chase and Simon (1973), Larkin, McDermott, Simon and Simon (1980), Schneider and Shiffrin (1977), Marcus, Cooper and Sweller (1996), Cooper, Tindall-Ford, Chandler and Sweller (2001). The literature and the reference are not extensive due to the length limitation of the paper.

4. Hypothesis

Understanding can be improved if we take into account the human cognitive architecture and the interaction of information in instructional design.

5. Conceptual Model

Information structure

We can find material to be learned that has a high or a low cognitive load. The level of interaction between the elements induces the level of cognitive load. Understanding is the ability to process all elements that interact.

Human cognitive architecture

•   Working memory
Working memory or also called short-term memory is limited in its capacity as well as in its duration. So it cannot process new high element interactivity material. It can be divided into “a visuo-spatial sketchpad for dealing with 2 dimensional diagrams or 3 dimensional information, a phonological loop for dealing with verbal information and a central executive as a coordinating processor.”
•   Long-term memory
Long-term memory is not just used for storage and recall of information. In fact it is of capital use regarding the processing of high cognitive material. Understanding depends on schemas held in the long-term memory.
•   Schemas
Due to the presence of schemas, elements of information can be categorized according to the manner in which they will be used. This allows the working memory to process high element interactivity material because it is treated as one single element, the schema.
•   Automation
Automation allows the use of less memory load to process information that has been well learned. Working memory can use the schemas which have incorporated the high interactivity elements through extensive learning in order to solve problems.

Some Instructional Effects

•   Split attention effect
This effect appears when it is better to physically integrate diagrams and statement rather than dissociate them. In fact this eliminates the search for referents.
•   The modality effect
The modality effect occurs when there is an increase in learning when presented one source in visual mode and the other in auditory mode rather than both in visual mode. In fact visual and auditory processors of working memory do not run fully separate. There are some synergies. So there is an increase in the total available working memory capacity.
•   The redundancy effect
The redundancy effect is found when adding redundant information. Rather than having a neutral or positive effect it has a negative effect regarding learning. In fact working memory resources will be required in order to determine that the information was redundant and so the working memory was unnecessarily used.
•   The element interactivity effect
The cognitive load effects that are presented above can only be obtained using high interactivity elements. In fact processing low interactivity elements does not affect the understanding because the working memory capacity may not be exceeded.
•   The imagination effect
When the schemas are acquired they can be used to imagine the procedures learned. This facilitates further learning trough automation for the learners with sufficient knowledge to process the high element interactivity material in working memory. For the others, the novice, studying is more efficient than imagining.

6. Experiment

This article is based on secondary research. There is no experiment presented.

7. Results

We can improve the understanding of the instructional designs by taking into account the information structure and the human cognitive architecture. The designs can be improved by taking advantage of the split-attention effect, modality effect and the imagination effect, avoiding the redundancy effect while taking into account the element interactivity effect.

8. Conclusion

The effects presented in this article can be useful for instructional design. But there are many other manners of doing instructional design which must also be taken into account.

9. Limits

This article limits itself to the author’s selected research. It does not provide a full view of instructional design, neither of cognitive architecture or information structure.

10. Future ways of research

Research of these effects when consulting a web page where cognitive load is not necessarily high but cognitive attention is low. What is actually remembered after consulting different types of information structure on web pages? What are the effects on the willingness to read the whole page?

11. Critic

This article is just a patchwork of research on information structure and cognitive architecture. This article does not investigate any new path or interpretation.

Interfirm Alliances in online Retailing

Posted on 04/26/2011 by Jean Eric PELET

Author(s) : Patrali Chatterjee

Interfirm Alliances in online Retailing

Patrali Chatterjee

Department of Marketing, Rutgers University, Newark, NJ 07102-1897, USA

LITERATURE REVIEW

The author of this article discusses the interfirm alliances in retailing, which he defines as contractual relationship undertaken by firms who perform complementary activities in facilitating marketing exchanges.

The author through his research on the topic tries to build on the popular media attestation to the fact that greater interconnectedness and competition of firms has been sparked by commercial development of the web.

Thus, the purpose and objective of the research is to investigate how satisfaction with performance and resource dependency in the presence of market and technology turbulence affects alliance outcomes.

The author further in the research examines the factors that contribute to successful alliances relationship as well as factors that affect alliance outcome.

The data for the research was collected through the use of questionnaire from selected firms within the online retailing sector. He explains that the limitation to sample within a single industry is to maintain homogeneity.

The research design is unique in that the author studies both partner of the alliance. Responses were correlated to detect cases where the partners colluded in answering the questionnaire. Usable data from 466 firms were collected after the return of questionnaires. The author identifies eight hypotheses to which he intends to confirm or repute.

The results of the research were set in tabular form which clearly presents the data and also compliments the research. The findings of the research support the notion that alliances succeeded when firms are satisfied with their own gains and partner firms performance.

The author concludes that the results from the research show that resource dependency and satisfaction with alliance partner and owns gains from the alliance determines whether a firm will continue in alliance.

The author intends to use the findings of the result for both practice and research purposes.

HYPOTHESIS

The author identified eight hypotheses which include:

Hypothesis A: Satisfaction with the partners’ performance has a positive effect on intention to continue with the alliance.

Hypothesis B: Satisfaction with firm’s gains from the alliance has a positive effect on intension to continue with alliance.

Hypothesis C: In the online retailing industry, satisfaction with firm’s gains from the alliance will have a stronger effect on the intension to continue with the alliance than satisfaction with partner performance.

Hypothesis D: Firms in the online retail industry that are relatively more dependent on their partners are more likely to continue with the alliance.

Hypothesis D1: Firms that primarily get market, product, and channel access are more likely to be dependent on their alliance partner than those who get revenue or marketing services.

Hypothesis D2: Firms that own both offline and online operations will be relatively less dependent on their alliance partner than pure play firms who own either an offline or online channel.

Hypothesis E: Firms that are involved in more alliance relationship are more likely to continue in the alliance than those involved I fewer alliances.

Hypothesis F: Firms that perceive greater technological turbulence affecting the online retailing industry are more likely to continue in an alliance.

Hypothesis G: Firms that perceive greater market turbulence affecting the online retailing industry are less likely to continue in an alliance.

Hypothesis H: The effect of resources dependency on intension to continue in an alliance would be lower for firms that perceive greater (a) market turbulence and (b) technological turbulence.

EXPERIMENT

Scales

The research made use of-

1.Five point scale. Scale 1-5 with 1 as poor and 5 as excellent.

2.Binary for each variable.

Dependent Variable

In the alliance equation, the dependent variable is – Intension to continue in alliance.

Independent Variables

The independent variables are: main effect of satisfaction with own gains and partner performance, involvement in other alliances, relative dependency and impetus for alliance, the hypothesized moderator effects of technological and market turbulence.

RESULTS

The result or findings from the research support the notion that alliances succeed when firms are satisfied with their own gains and partner firm performance.

CONCLUSION

The author concluded that the result suggest that resource dependency, satisfaction with alliance partner and own gains from the alliance determine whether a firm will continue in an alliance. Also,that the analyses of primary impetus for forming alliance relationships indicates that alliances that primarily involve merging of products, service and content, and fulfillment capabilities are more likely to survive.

CRITIC

Non return of questionnaires. The research questionnaires were sent out to 3167 alliance partner but only 446 were returned which is not up to half of the sample used. There may be the problem of inadequate representation to enable the author to generalise result.

REFERENCES

Anderson,J.C and Narus, J.A (1990) A model of distributor firm and manufacturer firm working partnerships. Vol.54 p.42-58.

Chatterpee, P (2002) Interfirm alliances in online retailing. Journal of business research . Vol.57 p.714-723