{"title":"When and how to use a “fighter brand” to combat a low-price entry","authors":"D. Deneffe, H. Vantrappen","doi":"10.1108/sl-01-2022-0002","DOIUrl":"https://doi.org/10.1108/sl-01-2022-0002","url":null,"abstract":"\u0000Purpose\u0000Managers have become wary of launching fighter brands. But they should not give up on a fighter brand strategy altogether: under certain conditions a fighter brand can be effective, if it is correctly positioned.\u0000\u0000\u0000Design/methodology/approach\u0000The authors’ decision-making framework to help managers think through the specific design of a fighter brand is supported by field experience in designing and successfully launching fighter brands. 10; The framework takes managers through four steps. 10;\u0000\u0000\u0000Findings\u0000A fighter brand can be designed to combat, and ideally eliminate, low-price competitors while protecting an organization’s premium-price offerings.\u0000\u0000\u0000Practical implications\u0000Identifying must-have features “must-haves” is at the core of the fighter brand framework.\u0000\u0000\u0000Originality/value\u0000If a company’s strategists can identify at least one unique must-have feature for the value segment with high certainty, and remove it from the fighter brand targeted at the price segment, the risk of cannibalization is minimal.\u0000","PeriodicalId":169963,"journal":{"name":"Strategy & Leadership","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133005711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Ziegler, L. Williams, Roberto Reis, Joan E. Klingel, Douglas J. McReynolds, Philip J. Gallagher, Edward H. Friedman, Klaus M. Rarisch, P. Thorpe, A. Nilsen, L. Dowling, M. Siegel, Lillie P. Howard, William L. Hendrickson, P. Spartano, S. Dworkin, Ingeborg M. Kohn, Michael E. Williams, Ingeborg L. Carlson, D. W. Foster, L. B. Croft, James Karmon, James P. Gilroy, K. Isbell
{"title":"Editor's Letter","authors":"R. Ziegler, L. Williams, Roberto Reis, Joan E. Klingel, Douglas J. McReynolds, Philip J. Gallagher, Edward H. Friedman, Klaus M. Rarisch, P. Thorpe, A. Nilsen, L. Dowling, M. Siegel, Lillie P. Howard, William L. Hendrickson, P. Spartano, S. Dworkin, Ingeborg M. Kohn, Michael E. Williams, Ingeborg L. Carlson, D. W. Foster, L. B. Croft, James Karmon, James P. Gilroy, K. Isbell","doi":"10.3905/jfi.2000.390843","DOIUrl":"https://doi.org/10.3905/jfi.2000.390843","url":null,"abstract":"his issue of The Journal of Fixed Income is a fine symposium on the mortgage markets. Our lead article, by Arora, Heike, and Mattu, examines risk and return in mortgages from 1989 to 1999. The authors find average excess returns of 28 basis points versus the average index option-adjusted spread estimate of 77 basis points. They find that mortgage excess returns are highly correlated with those on investment-grade bonds. Additionally, mortgage spreads widen when rates fall and prepayment risk is high, so investors should hedge mortgages to only 80% of model durations. Next, Hayre, Chaudhary, and Young present an excellent current analysis of mortgage prepayments. This article is written simply enough to be accessible to those who do not analyze mortgages full-time, yet is thorough and contains enough new analysis to be of interest to those researchers who do focus on mortgages. Jegadeesh and Ju’s article presents their impressive non-parametric statistical analysis of prepayments using the “generalized additive model,” which handles the non-linearities of mortgages particularly well. Their model fits mortgage prepayments significantly better than other published models. Clapp, Harding, and LaCour-Little combine data on mortgage terminations with housing market data to separate borrowers who prepay due to mobility from those who prepay without moving. Borrowers with high expected mobility are found to be less likely to refinance. Poor credit scores and high loan-to-value ratios inhibit financings. Dynkin, Hyman, Konstantinovsky, and Mattu demonstrate a dynamic rebalancing strategy for mortgages, which produces an approximately constant-duration return series. They find that this constant-duration strategy retains most of the mortgage alpha, while having a tracking error similar to that for other spread products. Our concluding article is by Peterson, Pietranico, Riepe, and Vroom, who examine bond mutual funds. They find a positive correlation of fund performance with past performance and a negative correlation of performance with expenses, given a large database of mutual funds. We hope you enjoy this issue of JFI.","PeriodicalId":169963,"journal":{"name":"Strategy & Leadership","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123500006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}