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  • Know Your City’s Marketplace Leverage

    I’ve noticed so often that urbanist policy suggestions or case studies are treated as universals. That is, with a presumption that a good idea or policy can be replicated pretty much anywhere. Clearly, there are a number of items like bike lanes and trails that would appear to be widely applicable, and for which the best practice standards would appear to work without much modification in most places. On the other hand, this isn’t true of everything.

    Where do most urban progressive policy ideas come from? From what I’ve seen, these tend to get wide currency when the come from one of the major urbanist citadels like London, New York, Washington, San Francisco, or Portland. This doesn’t always mean that was the place that came up with the idea, but it often is. But these cities are very different from your average, workaday type place.

    One problem with our analysis of these things is that they seldom take into account the amount of marketplace leverage a particular place has. Let’s take New York, for example. That’s a city with immense marketplace leverage, meaning that people and businesses are willing to put up with enormous cost and hassles to live, work, and do business there. In particular, the finance industry, which remains heavily centralized in New York as one of the two top global finance centers, generates tons and tons of cash. Most places don’t have that. It’s similar for tech in the Bay Area, government in Washington, DC, etc. These places have high value industries that are bound to the geography they are located and generate immense wealth and tax revenue. That means these places can get away with a lot of things other cities can’t. They’ve got a cash register that never stops ringing.

    One current case study is Seattle’s raising of the minimum wage to $15. First the small city of SeaTac raised its minimum wage to that level. SeaTac has 27,000 residents, but also includes SeaTac airport as the name implies. Airports employ a large service class who can benefit from a minimum wage increase. And most airport service businesses don’t have the luxury of moving off airport. That gave SeaTac marketplace leverage to raise the minimum wage significantly without huge risk to its employment base. SeaTac airport isn’t going anywhere.

    The city of Seattle itself has followed suit with a graduated increase to $15/hr. Again, Seattle is, like San Francisco, a city of the elite or on its way. The cost of doing business there is such that most businesses that are cost sensitive are already gone or on their way out the door. The coffee shops and other establishments with lower paid workforces mostly can’t move without losing their customer base. So in my view Seattle also has more leverage than your average city in setting this policy.

    It would be tempting to look at the Seattle case and say that other cities should raise their minimum wage. But for places without the concomitant marketplace leverage, it could prove to be economically disastrous.

    So understanding that degree of marketplace leverage you have is critical to evaluating local policies where the result could affect competitive positioning. Cities with greater marketplace leverage will have more flexibility to have local specific policies that might otherwise disadvantage them by raising costs, regulatory hurdles, etc. They can afford to be in the vanguard of policy experimentation.

    Places that fail to take stock of this do so at their peril. One place that has clearly done that is Rhode Island. It has basically acted like it’s entitled to put into place the same sorts of policies as next door Massachusetts and Connecticut, but without the captive high value industries to finance it. Massachusetts has the global power of greater Boston with its unmatched universities, tech, and biotech clusters. Connecticut has access to New York money. Rhode Island doesn’t have anything like this.

    Unfortunately for the Ocean State, it doesn’t seem to get it. I think in part that’s because the state’s intellectual elite – its cultural 1%, so to speak – live in a different reality. Many of them have lived and worked elsewhere like Manhattan and chose to move to Providence for lifestyle. Or they are affiliated with Brown or RISD, two atolls of actual competitive advantage in the state. They look around and see that they are in Rhode Island and they can compete at the global level, so they push for the same sorts of ideas that they used to have back when they actually did live in Manhattan or wherever, without realizing that the other 99% of Rhode Island can’t compete at that level.

    Back in early 2013, I summed it up like this:

    The basic problem of Providence (and by extension the rest of Rhode Island) becomes obvious: it is a small city, without an above average talent pool or assets, but with high costs and business-unfriendly regulation. Thus Providence will neither be competitive with elite talent centers like Boston, nor with smaller city peers like Nashville that are low cost and nearly “anything goes” from a regulatory perspective.

    One reason it’s unlikely they’ll escape from this dilemma is that in my view they aren’t ready to face up to the reality of where they stand in the market competitively.

    Acting like you have leverage when you don’t can be a serious problem, but you can also “leave money on the table” when you do have leverage and fail to take advantage of it. Just as one example, Indianapolis has a “beggar’s mentality” when it comes to development. It just so happens that because of the tourism/sports business and the locals penchant for chain dining that upscale national chains have some of their best locations anywhere in downtown Indianapolis. It’s literally one of the most profitable places in the country for that kind of business – not that you’d know it from the way the city treats them.

    As one example, a BW-3 was built on Washington St. downtown a couple years back. As it turned out, they built something contrary to their approved plans and which violated numerous design guidelines of the city. Did the city make them fix it? Nope. So BW-3′s insult to streetscape humanity was allowed to stand. The city had a lot of marketplace leverage in this case, but didn’t recognize it or wasn’t willing to use it.

    The lesson here is that you need to take stock of the amount of marketplace leverage you have, and tailor your approach accordingly. This is part of coming up with an urban solution set that is right for a specific place and not just a bunch of imported ideas from elsewhere pursued without thought.

    Also, cities should also be asking what they can do to add to their marketplace leverage. Hopefully over time as they continuously improve, their intrinsic attractiveness will go up, which will accrue leverage benefits right there.

    Aaron M. Renn is an independent writer on urban affairs and the founder of Telestrian, a data analysis and mapping tool. He writes at The Urbanophile, where this piece originally appeared.

    Top Photograph: Downtown Seattle from the Space Needle (by Wendell Cox)

  • Pret personnel

  • The Cities Winning The Battle For Information Jobs 2014

    In the town of Verona on the rural fringes of Madison, Wisc., there’s a Google-like campus that houses one of the country’s most rapidly growing tech companies, and one of the least well known. Founded in 1979, the medical software maker Epic has grown to employ 6,800 people, most of whom work at its 5.5 million-square-foot headquarters complex, which sprawls over 800 acres of what was farmland until the early 1990s.

    Despite annual revenue estimated at $1.5 billion, the company is congenitally publicity shy, a characteristic associated with its founder and CEO, Judy Faulkner. Yet in its quiet, unassuming way, Epic is emblematic of the expansion of the information industry in the Madison area. Employment in the metropolitan area’s information sector is up 28% since 2008, among the fastest growth in the country over that period. This has occurred despite the city’s reputation for left-wing, often anti-business politics—a culture that its left-leaning mayor (and Epic booster), Paul Soglin, describes as “76 square miles surrounded by reality.”

    To come up with our list of the cities with the fastest-growing information sectors, we zeroed in on the 55 metropolitan statistical areas that have at least 10,000 information jobs, which includes software, publishing, broadcasting and telecommunications services. We used the same methodology as for our overall ranking of the Best Cities for Jobs: we ranked the MSAs based on job growth in the sector over the long-term (2002-13), mid-term (2008-13) and the last two years, as well as recent momentum.

    View the Best Cities for Information Jobs 2014 List

    Our top 10 is dominated by large metro areas renowned as tech hubs – Madison, at No. 5,  is the smallest by far. In first place is Silicon Valley — San Jose-Sunnyvale-Santa Clara — followed by San Francisco-San Mateo-Redwood City, which together employ over 110,000 information workers. Both have been primary winners in the latest high-tech bubble. Since 2008 information employment is up 23% in San Jose and 27% in San Francisco.

    They’re followed by Boston-Cambridge-Quincy in third place, and Austin-Round Rock-San Marcos, Texas in fourth. The foundation built in previous tech booms — including venture capital, educational institutions, corporate headquarters, and skilled workers — has helped many of the strongest tech regions become even more so this go around.

    But there are some surprising places on our list, including a few Sun Belt metro areas that were hard hit in the housing bust. Take Atlanta-Sandy Springs-Marietta, Ga., which ranks sixth on our list, with a 7.7% expansion in information employment since 2010. Less expensive than the West Coast hotbeds or Boston, Atlanta could be emerging as a player in the sector. Last year General Motors opened a software facility in suburban Roswell, with plans to create over 1,000 new jobs.

    Phoenix-Mesa-Glendale, Ariz., ranks ninth with 11% growth in information employment since 2008. In 2013, the metro area added as many information jobs, roughly 2,000, as the Bay Area, according to an Arizona State University study.

    The Big Players

    Historically, information jobs have clustered in the nation’s largest metropolitan areas. Los Angeles still leads the nation with 201,000 information jobs, while New York is No. 2 with 182,000.

    Yet the fortunes of the biggest players appear to be changing. New York ranks a respectable 13th on our list of the fastest-growing cities for information jobs, with a 7.7% expansion since 2008. This reflects not only the growth of the city’s relatively small tech sector but also its robust film, television and media industries. Los Angeles-Long Beach-Santa Ana, however, has not fared nearly so well, ranking a middling 27th, on our list. This reflects, in part, the erosion of the region’s once dominant entertainment industry. This is particularly true of feature films, where production has dropped 50% from 1996 levels. Since 2000, L.A. has lost 9,000 entertainment industry jobs, leaving it with 132,000.

    With tech companies such as Apple and Google targeting content, and the massive shift of readers over to the web, the preeminence of New York and Los Angeles could continue to erode over time.

    This shift can be seen in the growing forays of the Valley into film and television production through companies such as Netflix and Google’s YouTube, as well as in the already longstanding decline of the music industry — undermined by both legal and illegal forms of music distribution online.

    Information Jobs Set To Disperse

    For New York, a more worrisome development is the massive decline of newspaper, magazine and book industry employment. At a time when Google alone reaps more advertising revenues than the entire newspaper business, it’s not surprising that media growth is shifting toward the Left Coast. Since 2001, the book publishing industry, dominated by New York, has contracted nationally by 17,000 jobs. Newspapers lost 190,000 positions and magazines 50,000 in that same span. But internet publishing, dominated by the Bay Area, expanded by 77,000 jobs during the same window.

    In many ways, the recent tech boom, with its emphasis on social media, has been a blessing to high-cost areas such as Silicon Valley, San Francisco and even New York. Yet at the same time, as we have seen in our other jobs lists, the information sector is expanding most rapidly in some fairly unexpected places. Some of the fastest growers on a percentage basis are still minor players– Janesville, Wisc., Lansing, Mich., and Flint Mich. –  and are tied largely to the up and downs of the manufacturing sector.

    But some, like Madison, are heading toward critical mass. Provo-Orem, Utah, for example, with some 9,800 information jobs, did not make the 10,000 job cut for our list, but should soon given its 21% growth since 2008. Others are in regions just outside the main information hubs, including Santa Barbara-Santa Maria-Goleta, north of Los Angeles, and San Luis Obispo, south of San Jose, as well as Bridgeport-Stamford-Norwalk, north of New York, and Durham-Chapel Hill, N.C., just outside Raleigh-Cary. There has also been rapid information job growth in Huntsville, Ala., a tech center that built up around NASA, and Baton Rouge, La., which has benefited from growth in energy and manufacturing along the lower Mississippi.

    Ultimately, price pressures, particularly on housing, are likely to feed growth in some of these emerging regions. In this way, what is happening in Madison foreshadows the growth of a whole series of new information hotbeds. These may not challenge Silicon Valley, New York or Hollywood in the near future, but they are likely to make their presence known as information jobs continue to spread to fast-growing and more affordable regions.

    View the Best Cities for Information Jobs 2014 List

    This story originally appeared at Forbes.

    Joel Kotkin is executive editor of NewGeography.com and Distinguished Presidential Fellow in Urban Futures at Chapman University, and a member of the editorial board of the Orange County Register. He is author of The City: A Global History and The Next Hundred Million: America in 2050. His most recent study, The Rise of Postfamilialism, has been widely discussed and distributed internationally. He lives in Los Angeles, CA.

    Michael Shires, Ph.D. is a professor at Pepperdine University School of Public Policy.

    Madison, Wisconsin photo by Patrick43470.

  • Midsize Cities Information Jobs – 2014 Best Cities Rankings

    View the Best Cities for Information Jobs 2014 List

    2014 MSA Info  Ranking – Midsized MSAs Area 2014 Weighted INDEX 2013 Information Employment 20012-13 Info Growth 2014 Ranking Change from 2013 – Midsized MSAs
    1 Provo-Orem, UT 93.0                  9.8 10.5% 3
    2 Lansing-East Lansing, MI 90.3                  3.2 5.4% 1
    3 Madison, WI 85.5                12.6 1.9% 2
    4 Santa Barbara-Santa Maria-Goleta, CA 84.7                  4.3 -0.8% (2)
    5 Bridgeport-Stamford-Norwalk, CT NECTA 83.7                12.0 5.9% 13
    6 Baton Rouge, LA 83.2                  5.5 6.4% 1
    7 Huntsville, AL 82.8                  2.7 3.8% 2
    8 Durham-Chapel Hill, NC 79.0                  3.7 2.8% 3
    9 Charleston-North Charleston-Summerville, SC 78.4                  5.2 2.0% 20
    10 Augusta-Richmond County, GA-SC 77.7                  3.1 5.6% 70
    11 El Paso, TX 77.2                  5.8 -2.8% 13
    12 Boise City-Nampa, ID 74.6                  4.5 3.1% 29
    13 Lincoln, NE 73.1                  2.5 -1.3% 59
    14 Worcester, MA-CT NECTA 71.8                  3.6 0.0% 9
    15 Springfield, MA-CT NECTA 71.0                  3.9 6.3% 13
    16 Tallahassee, FL 69.6                  3.4 2.0% 10
    17 Spokane, WA 69.0                  2.9 -3.3% (1)
    18 Tacoma, WA Metropolitan Division 69.0                  2.9 3.6% 55
    19 Knoxville, TN 68.7                  5.6 -0.6% 8
    20 McAllen-Edinburg-Mission, TX 68.7                  2.1 -1.6% 23
    21 Ann Arbor, MI 68.2                  4.1 2.5% 12
    22 Jackson, MS 67.7                  4.7 -3.4% (12)
    23 Grand Rapids-Wyoming, MI 64.8                  4.4 3.1% 30
    24 Allentown-Bethlehem-Easton, PA-NJ 63.9                  6.2 2.2% 21
    25 Cape Coral-Fort Myers, FL 63.1                  3.1 1.1% 12
    26 Gary, IN Metropolitan Division 62.8                  2.1 3.3% 14
    27 Greenville-Mauldin-Easley, SC 62.0                  6.7 -0.5% (10)
    28 Akron, OH 61.5                  3.9 1.7% 20
    29 Santa Rosa-Petaluma, CA 61.3                  2.6 2.6% (15)
    30 Montgomery, AL 60.3                  2.2 0.0% 2
    31 Columbia, SC 60.3                  5.4 -0.6% 36
    32 York-Hanover, PA 60.2                  1.8 1.9% (11)
    33 Winston-Salem, NC 59.4                  2.0 3.5% 44
    34 Springfield, MO 58.9                  3.9 2.7% 0
    35 Anchorage, AK 58.5                  4.5 1.5% 25
    36 Mobile, AL 57.6                  2.0 1.7% 27
    37 Toledo, OH 57.3                  3.4 -1.0% (12)
    38 Asheville, NC 56.6                  1.9 0.0% (26)
    39 Ogden-Clearfield, UT 56.4                  2.1 -3.1% (33)
    40 Boulder, CO 56.3                  8.4 0.0% (10)
    41 Oxnard-Thousand Oaks-Ventura, CA 56.3                  5.1 -1.9% (2)
    42 Corpus Christi, TX 54.6                  2.1 -1.6% 14
    43 Fort Wayne, IN 54.6                  3.3 -3.0% (30)
    44 Trenton-Ewing, NJ 53.6                  5.4 -4.1% (43)
    45 North Port-Bradenton-Sarasota, FL 52.1                  3.3 -1.0% 24
    46 Fresno, CA 50.7                  3.8 0.9% (26)
    47 Bakersfield-Delano, CA 50.2                  2.5 -7.4% (28)
    48 Davenport-Moline-Rock Island, IA-IL 46.7                  2.5 0.0% 17
    49 Shreveport-Bossier City, LA 45.9                  2.4 1.4% 8
    50 Tucson, AZ 44.2                  4.3 1.6% 0
    51 Framingham, MA  NECTA Division 44.0                  5.3 -3.6% (15)
    52 Kansas City, KS 43.4                15.2 3.2% (6)
    53 Canton-Massillon, OH 43.4                  1.7 0.0% (9)
    54 Lexington-Fayette, KY 42.8                  5.6 -5.1% 4
    55 Albany-Schenectady-Troy, NY 42.4                  8.3 -3.1% (6)
    56 Colorado Springs, CO 42.2                  6.9 -5.0% (21)
    57 Chattanooga, TN-GA 41.9                  2.8 -2.3% 30
    58 Harrisburg-Carlisle, PA 40.7                  4.9 1.4% 18
    59 Fayetteville-Springdale-Rogers, AR-MO 40.6                  1.8 -3.5% 9
    60 Green Bay, WI 38.5                  1.9 -3.4% (9)
    61 Lancaster, PA 37.7                  3.1 0.0% 9
    62 Calvert-Charles-Prince George’s, MD 37.4                  5.2 -5.5% (47)
    63 Lafayette, LA 37.2                  2.5 -5.1% 22
    64 Savannah, GA 37.1                  1.3 -4.8% 0
    65 Peoria, IL 35.2                  2.2 -8.3% (34)
    66 Syracuse, NY 34.4                  4.5 -3.6% (12)
    67 Tulsa, OK 33.6                  7.7 -2.5% (8)
    68 Little Rock-North Little Rock-Conway, AR 33.3                  7.1 -2.3% 14
    69 Albuquerque, NM 32.9                  7.4 -7.9% (61)
    70 Reading, PA 32.7                  1.3 -4.9% (48)
    71 Beaumont-Port Arthur, TX 31.2                  1.4 -2.3% 7
    72 Pensacola-Ferry Pass-Brent, FL 30.8                  2.3 -2.8% 12
    73 Poughkeepsie-Newburgh-Middletown, NY 30.0                  3.6 -2.7% (2)
    74 Lakeland-Winter Haven, FL 29.3                  1.5 -4.2% (19)
    75 Lake County-Kenosha County, IL-WI Metro Div 28.1                  3.7 -5.1% (37)
    76 Greensboro-High Point, NC 26.2                  4.9 -7.0% (34)
    77 Roanoke, VA 25.5                  1.7 -5.5% (15)
    78 Wichita, KS 25.3                  4.3 0.0% 12
    79 Deltona-Daytona Beach-Ormond Beach, FL 23.8                  1.8 -6.9% (32)
    80 Stockton, CA 23.5                  1.9 -6.6% 3
    81 Portland-South Portland-Biddeford, ME NECTA 22.2                  3.1 -2.1% 10
    82 Evansville, IN-KY 21.3                  1.9 -3.4% (3)
    83 Des Moines-West Des Moines, IA 21.3                  7.0 -2.8% (17)
    84 Baltimore City, MD 20.9                  3.8 -4.2% (32)
    85 Wilmington, DE-MD-NJ Metropolitan Division 20.5                  4.4 -4.3% (10)
    86 Dayton, OH 19.7                  8.5 -3.8% 0
    87 Palm Bay-Melbourne-Titusville, FL 17.4                  1.9 -5.0% (26)
    88 Youngstown-Warren-Boardman, OH-PA 17.3                  2.0 -3.2% 1
    89 Reno-Sparks, NV 16.9                  1.9 -3.4% (8)
    90 Scranton–Wilkes-Barre, PA 13.3                  3.8 -3.4% (16)
    91 Modesto, CA 12.1                  0.9 0.0% 0
    92 New Haven, CT NECTA 9.5                  4.1 -4.7% (4)

  • Large Cities Information Jobs – 2014 Best Cities Rankings

    View the Best Cities for Information Jobs 2014 List

    2014 MSA Info  Ranking – LARGE MSAs Area Weighted INDEX 2013 Information Employment 20012-13 Info Growth 2014  Change from 2013 – Large MSAs
    1 San Jose-Sunnyvale-Santa Clara, CA 96.4                60.8 9.2% 0
    2 Austin-Round Rock-San Marcos, TX 90.7                23.6 2.6% 3
    3 San Francisco-San Mateo-Redwood City, CA Metro Div 89.5                52.3 3.2% (1)
    4 Phoenix-Mesa-Glendale, AZ 84.9                33.7 4.1% 5
    5 New York City, NY 84.3             181.8 3.3% 8
    6 Boston-Cambridge-Quincy, MA NECTA Division 80.1                59.5 2.5% (2)
    7 San Antonio-New Braunfels, TX 79.9                20.9 3.6% 0
    8 Columbus, OH 79.5                18.2 2.8% 21
    9 Salt Lake City, UT 78.2                18.5 -2.8% 8
    10 Seattle-Bellevue-Everett, WA Metro Div 78.0                88.0 1.7% 5
    11 Raleigh-Cary, NC 77.8                18.1 2.3% (3)
    12 Los Angeles-Long Beach-Glendale, CA Metro Div 77.7             201.5 2.3% 16
    13 Indianapolis-Carmel, IN 77.5                16.1 1.5% 1
    14 Portland-Vancouver-Hillsboro, OR-WA 77.3                23.1 1.3% 13
    15 Fort Lauderdale-Pompano Beach-Deerfield Beach, FL Metro Div 76.7                18.8 2.4% (3)
    16 Atlanta-Sandy Springs-Marietta, GA 76.7                85.0 1.4% (10)
    17 Charlotte-Gastonia-Rock Hill, NC-SC 75.2                22.2 1.4% (6)
    18 New Orleans-Metairie-Kenner, LA 73.3                  8.1 -8.6% (15)
    19 Nashville-Davidson–Murfreesboro–Franklin, TN 72.6                20.3 1.2% (9)
    20 Warren-Troy-Farmington Hills, MI Metro Div 71.1                19.7 1.2% (4)
    21 Dallas-Plano-Irving, TX Metro Div 69.4                66.6 3.0% 9
    22 Orlando-Kissimmee-Sanford, FL 68.8                23.9 2.0% 20
    23 Houston-Sugar Land-Baytown, TX 68.2                32.7 2.8% 1
    24 West Palm Beach-Boca Raton-Boynton Beach, FL Metro Div 67.8                  9.6 1.8% 16
    25 St. Louis, MO-IL 66.3                29.6 1.0% 0
    26 Las Vegas-Paradise, NV 65.3                  9.7 -4.3% (4)
    27 Louisville-Jefferson County, KY-IN 64.7                  9.5 -0.3% (8)
    28 Hartford-West Hartford-East Hartford, CT NECTA 64.2                11.0 -2.4% 17
    29 Minneapolis-St. Paul-Bloomington, MN-WI 62.5                38.7 -0.3% (8)
    30 Santa Ana-Anaheim-Irvine, CA Metro Div 62.2                25.6 3.2% 7
    31 Denver-Aurora-Broomfield, CO 61.7                43.4 0.2% 2
    32 Cincinnati-Middletown, OH-KY-IN 61.2                14.0 -1.2% 3
    33 Chicago-Joliet-Naperville, IL Metro Div 60.7                74.6 -0.2% (13)
    34 Miami-Miami Beach-Kendall, FL Metro Div 57.0                18.1 0.0% (3)
    35 Omaha-Council Bluffs, NE-IA 55.9                11.0 -0.3% (17)
    36 Honolulu, HI 55.8                  7.1 -3.2% 10
    37 Tampa-St. Petersburg-Clearwater, FL 55.5                26.0 0.1% 11
    38 Pittsburgh, PA 54.7                18.5 -0.5% (12)
    39 Detroit-Livonia-Dearborn, MI Metro Div 50.5                  7.4 3.2% 21
    40 Buffalo-Niagara Falls, NY 48.9                  7.4 -1.8% (8)
    41 Philadelphia City, PA 48.7                11.5 -3.6% (18)
    42 Cleveland-Elyria-Mentor, OH 48.4                15.1 -0.4% 5
    43 Jacksonville, FL 47.4                  9.1 -0.4% 9
    44 Nassau-Suffolk, NY Metro Div 46.5                23.6 -2.2% (5)
    45 Memphis, TN-MS-AR 44.9                  6.0 0.6% (1)
    46 Milwaukee-Waukesha-West Allis, WI 44.1                14.5 -1.4% 5
    47 Edison-New Brunswick, NJ Metro Div 43.4                24.2 -2.9% (13)
    48 Riverside-San Bernardino-Ontario, CA 43.0                11.2 -2.0% 16
    49 Washington-Arlington-Alexandria, DC-VA-MD-WV Metro Div 42.3                61.4 -1.7% 1
    50 Birmingham-Hoover, AL 41.7                  8.8 -0.8% 9
    51 Northern Virginia, VA 40.1                38.9 -1.7% (2)
    52 Providence-Fall River-Warwick, RI-MA NECTA 39.2                10.0 -4.1% 4
    53 San Diego-Carlsbad-San Marcos, CA 38.9                24.0 -1.8% (17)
    54 Bergen-Hudson-Passaic, NJ 38.7                17.3 -2.4% 1
    55 Fort Worth-Arlington, TX Metro Div 38.6                13.2 -2.9% (1)
    56 Bethesda-Rockville-Frederick, MD Metro Div 37.5                13.7 -4.8% (13)
    57 Newark-Union, NJ-PA Metro Div 36.6                18.5 -1.8% (19)
    58 Kansas City, MO 36.5                14.7 -1.6% 3
    59 Virginia Beach-Norfolk-Newport News, VA-NC 36.4                11.2 -2.9% (2)
    60 Richmond, VA 35.0                  8.1 2.1% 5
    61 Putnam-Rockland-Westchester, NY 34.7                12.6 -2.1% (8)
    62 Oakland-Fremont-Hayward, CA Metro Div 33.4                21.4 -2.3% (4)
    63 Rochester, NY 30.9                  8.4 -6.7% (22)
    64 Sacramento–Arden-Arcade–Roseville, CA 28.3                14.7 -4.5% (1)
    65 Camden, NJ Metro Div 24.8                  6.2 -9.7% 1
    66 Oklahoma City, OK 17.1                  8.1 -2.4% (4)

  • All Cities Information Jobs – 2014 Best Cities Rankings

    View the Best Cities for Information Jobs 2014 List

    2014 MSA Info Overall Ranking Area Weighted INDEX 2013 Information Employment 20012-13 Info Growth 2014  Change from 2013 –
    All MSAs
    1 Janesville, WI 97.9                  1.5 18.4% 121
    2 Flint, MI 97.3                  4.2 9.5% 1
    3 San Jose-Sunnyvale-Santa Clara, CA 96.4                60.8 9.2% (1)
    4 Logan, UT-ID 93.3                  0.9 12.5% 12
    5 Provo-Orem, UT 93.0                  9.8 10.5% 6
    6 Austin-Round Rock-San Marcos, TX 90.7                23.6 2.6% 12
    7 Lansing-East Lansing, MI 90.3                  3.2 5.4% 3
    8 San Francisco-San Mateo-Redwood City, CA Metro Div 89.5                52.3 3.2% (3)
    9 Abilene, TX 88.2                  1.2 9.1% 74
    10 Laredo, TX 88.1                  0.7 16.7% 26
    11 San Luis Obispo-Paso Robles, CA 87.3                  1.4 7.7% 34
    12 Rochester, MN 87.2                  1.7 6.2% 2
    13 Fond du Lac, WI 86.5                  0.9 12.5% 198
    14 Madison, WI 85.5                12.6 1.9% 5
    15 Phoenix-Mesa-Glendale, AZ 84.9                33.7 4.1% 15
    16 Santa Barbara-Santa Maria-Goleta, CA 84.7                  4.3 -0.8% (8)
    17 College Station-Bryan, TX 84.5                  1.3 0.0% (13)
    18 New York City, NY 84.3             181.8 3.3% 22
    19 Portsmouth, NH-ME NECTA 84.0                  2.0 1.7% 9
    20 Bridgeport-Stamford-Norwalk, CT NECTA 83.7                12.0 5.9% 43
    21 Baton Rouge, LA 83.2                  5.5 6.4% 8
    22 Huntsville, AL 82.8                  2.7 3.8% 11
    23 Lafayette, IN 80.5                  1.1 6.5% 42
    24 Tyler, TX 80.3                  2.3 2.9% (15)
    25 Boston-Cambridge-Quincy, MA NECTA Division 80.1                59.5 2.5% (8)
    26 Champaign-Urbana, IL 80.1                  2.5 10.4% 236
    27 San Antonio-New Braunfels, TX 79.9                20.9 3.6% (5)
    28 Columbus, OH 79.5                18.2 2.8% 70
    29 Durham-Chapel Hill, NC 79.0                  3.7 2.8% 9
    30 Charleston-North Charleston-Summerville, SC 78.4                  5.2 2.0% 73
    31 Salt Lake City, UT 78.2                18.5 -2.8% 31
    32 Seattle-Bellevue-Everett, WA Metro Div 78.0                88.0 1.7% 18
    33 Raleigh-Cary, NC 77.8                18.1 2.3% (10)
    34 Los Angeles-Long Beach-Glendale, CA Metro Div 77.7             201.5 2.3% 57
    35 Augusta-Richmond County, GA-SC 77.7                  3.1 5.6% 221
    36 Indianapolis-Carmel, IN 77.5                16.1 1.5% 5
    37 Portland-Vancouver-Hillsboro, OR-WA 77.3                23.1 1.3% 52
    38 El Paso, TX 77.2                  5.8 -2.8% 55
    39 Fort Lauderdale-Pompano Beach-Deerfield Beach, FL Metro Div 76.7                18.8 2.4% 0
    40 Atlanta-Sandy Springs-Marietta, GA 76.7                85.0 1.4% (19)
    41 Hickory-Lenoir-Morganton, NC 75.6                  1.0 0.0% (21)
    42 Charlotte-Gastonia-Rock Hill, NC-SC 75.2                22.2 1.4% (5)
    43 Cheyenne, WY 75.1                  1.1 0.0% (42)
    44 Boise City-Nampa, ID 74.6                  4.5 3.1% 98
    45 Binghamton, NY 74.6                  1.9 11.8% 75
    46 Sebastian-Vero Beach, FL 73.9                  0.7 0.0% 2
    47 New Orleans-Metairie-Kenner, LA 73.3                  8.1 -8.6% (40)
    48 Lincoln, NE 73.1                  2.5 -1.3% 184
    49 Oshkosh-Neenah, WI 72.9                  1.6 2.1% 22
    50 Nashville-Davidson–Murfreesboro–Franklin, TN 72.6                20.3 1.2% (16)
    51 Greenville, NC 72.6                  1.0 11.1% 44
    52 Bend, OR 72.4                  1.4 0.0% 154
    53 Saginaw-Saginaw Township North, MI 72.1                  1.4 7.7% 194
    54 Las Cruces, NM 71.9                  0.9 0.0% (12)
    55 Worcester, MA-CT NECTA 71.8                  3.6 0.0% 37
    56 Auburn-Opelika, AL 71.7                  0.5 0.0% 201
    57 Flagstaff, AZ 71.6                  0.4 0.0% 0
    58 Warren-Troy-Farmington Hills, MI Metro Div 71.1                19.7 1.2% (7)
    59 Springfield, MA-CT NECTA 71.0                  3.9 6.3% 43
    60 Lewiston, ID-WA 70.8                  0.4 0.0% 0
    61 Cleveland, TN 70.1                  0.3 0.0% (6)
    62 Bay City, MI 70.1                  0.5 25.0% 135
    63 Eugene-Springfield, OR 69.7                  3.3 0.0% 54
    64 Tallahassee, FL 69.6                  3.4 2.0% 33
    65 Dallas-Plano-Irving, TX Metro Div 69.4                66.6 3.0% 46
    66 Spokane, WA 69.0                  2.9 -3.3% (14)
    67 Tacoma, WA Metro Div 69.0                  2.9 3.6% 167
    68 Orlando-Kissimmee-Sanford, FL 68.8                23.9 2.0% 78
    69 Knoxville, TN 68.7                  5.6 -0.6% 30
    70 Kingsport-Bristol-Bristol, TN-VA 68.7                  2.1 0.0% 233
    71 McAllen-Edinburg-Mission, TX 68.7                  2.1 -1.6% 74
    72 Houston-Sugar Land-Baytown, TX 68.2                32.7 2.8% 9
    73 Muskegon-Norton Shores, MI 68.2                  0.8 14.3% 202
    74 Ann Arbor, MI 68.2                  4.1 2.5% 34
    75 West Palm Beach-Boca Raton-Boynton Beach, FL Metro Div 67.8                  9.6 1.8% 63
    76 Clarksville, TN-KY 67.7                  1.1 -3.0% (52)
    77 Jackson, MS 67.7                  4.7 -3.4% (42)
    78 Columbus, IN 67.6                  0.5 0.0% (63)
    79 Wilmington, NC 66.8                  2.9 2.4% 117
    80 St. Louis, MO-IL 66.3                29.6 1.0% 5
    81 Fargo, ND-MN 66.2                  3.3 3.1% 111
    82 Prescott, AZ 65.9                  0.6 0.0% (6)
    83 Burlington, NC 65.7                  0.5 0.0% 108
    84 Las Vegas-Paradise, NV 65.3                  9.7 -4.3% (7)
    85 Sherman-Denison, TX 65.2                  0.5 0.0% 130
    86 Bloomington, IN 65.0                  1.3 0.0% 1
    87 Rochester-Dover, NH-ME NECTA 64.8                  1.2 0.0% (61)
    88 Grand Rapids-Wyoming, MI 64.8                  4.4 3.1% 89
    89 St. Cloud, MN 64.8                  1.7 0.0% (10)
    90 Louisville-Jefferson County, KY-IN 64.7                  9.5 -0.3% (20)
    91 Glens Falls, NY 64.5                  1.0 3.4% (9)
    92 Hartford-West Hartford-East Hartford, CT NECTA 64.2                11.0 -2.4% 61
    93 Allentown-Bethlehem-Easton, PA-NJ 63.9                  6.2 2.2% 62
    94 Madera-Chowchilla, CA 63.7                  0.4 20.0% 43
    95 Haverhill-North Andover-Amesbury, MA-NH  NECTA Division 63.7                  0.9 -3.7% 40
    96 Pueblo, CO 63.4                  0.7 5.0% 61
    97 Cape Coral-Fort Myers, FL 63.1                  3.1 1.1% 29
    98 Gary, IN Metro Div 62.8                  2.1 3.3% 43
    99 Minneapolis-St. Paul-Bloomington, MN-WI 62.5                38.7 -0.3% (24)
    100 Yuma, AZ 62.4                  0.5 -16.7% (87)
    101 Sioux Falls, SD 62.2                  2.7 1.3% 109
    102 Santa Ana-Anaheim-Irvine, CA Metro Div 62.2                25.6 3.2% 26
    103 Greenville-Mauldin-Easley, SC 62.0                  6.7 -0.5% (42)
    104 Kokomo, IN 61.9                  0.4 0.0% (46)
    105 Naples-Marco Island, FL 61.7                  1.5 0.0% (11)
    106 Denver-Aurora-Broomfield, CO 61.7                43.4 0.2% 13
    107 Victoria, TX 61.6                  0.5 0.0% 166
    108 Akron, OH 61.5                  3.9 1.7% 57
    109 Santa Rosa-Petaluma, CA 61.3                  2.6 2.6% (63)
    110 Decatur, AL 61.3                  0.3 0.0% 51
    111 Ithaca, NY 61.3                  0.5 0.0% 5
    112 Cincinnati-Middletown, OH-KY-IN 61.2                14.0 -1.2% 11
    113 Altoona, PA 61.2                  0.9 4.0% 92
    114 Chicago-Joliet-Naperville, IL Metro Div 60.7                74.6 -0.2% (42)
    115 St. George, UT 60.6                  0.7 0.0% (83)
    116 Barnstable Town, MA NECTA 60.4                  1.6 0.0% (49)
    117 Montgomery, AL 60.3                  2.2 0.0% (10)
    118 Columbia, SC 60.3                  5.4 -0.6% 100
    119 York-Hanover, PA 60.2                  1.8 1.9% (39)
    120 Gadsden, AL 60.1                  0.4 22.2% 187
    121 Winston-Salem, NC 59.4                  2.0 3.5% 121
    122 Fort Collins-Loveland, CO 59.2                  2.4 0.0% (32)
    123 Manchester, NH NECTA 59.1                  3.1 -3.1% (55)
    124 Springfield, MO 58.9                  3.9 2.7% (15)
    125 Santa Fe, NM 58.8                  0.9 13.0% 181
    126 Killeen-Temple-Fort Hood, TX 58.6                  2.2 1.5% 13
    127 Grand Junction, CO 58.6                  0.8 0.0% 109
    128 Longview, TX 58.6                  1.4 0.0% (16)
    129 Anchorage, AK 58.5                  4.5 1.5% 66
    130 Yuba City, CA 58.5                  0.4 0.0% 18
    131 Fort Smith, AR-OK 58.1                  1.3 -4.9% (119)
    132 Lawton, OK 58.1                  0.5 0.0% 120
    133 Redding, CA 58.0                  0.6 5.6% 41
    134 Terre Haute, IN 57.7                  0.7 0.0% (33)
    135 Mobile, AL 57.6                  2.0 1.7% 66
    136 Toledo, OH 57.3                  3.4 -1.0% (40)
    137 South Bend-Mishawaka, IN-MI 57.2                  1.8 0.0% 71
    138 La Crosse, WI-MN 57.2                  1.1 0.0% (50)
    139 Miami-Miami Beach-Kendall, FL Metro Div 57.0                18.1 0.0% (25)
    140 Cedar Rapids, IA 56.9                  4.9 -0.7% (10)
    141 Fayetteville, NC 56.6                  1.5 0.0% 76
    142 Asheville, NC 56.6                  1.9 0.0% (99)
    143 Ogden-Clearfield, UT 56.4                  2.1 -3.1% (118)
    144 Boulder, CO 56.3                  8.4 0.0% (40)
    145 Texarkana, TX-Texarkana, AR 56.3                  0.5 0.0% 24
    146 Oxnard-Thousand Oaks-Ventura, CA 56.3                  5.1 -1.9% (17)
    147 Omaha-Council Bluffs, NE-IA 55.9                11.0 -0.3% (78)
    148 Honolulu, HI 55.8                  7.1 -3.2% 6
    149 Tampa-St. Petersburg-Clearwater, FL 55.5                26.0 0.1% 9
    150 Grand Forks, ND-MN 55.3                  0.6 0.0% 88
    151 Pittsburgh, PA 54.7                18.5 -0.5% (65)
    152 Corpus Christi, TX 54.6                  2.1 -1.6% 35
    153 Fort Wayne, IN 54.6                  3.3 -3.0% (109)
    154 Kankakee-Bradley, IL 54.5                  0.5 0.0% 162
    155 Port St. Lucie, FL 54.3                  1.4 5.1% 106
    156 Holland-Grand Haven, MI 53.9                  0.7 0.0% (92)
    157 Wichita Falls, TX 53.7                  1.1 10.0% 83
    158 El Centro, CA 53.7                  0.4 0.0% (102)
    159 Trenton-Ewing, NJ 53.6                  5.4 -4.1% (153)
    160 Coeur d’Alene, ID 53.0                  0.7 16.7% 135
    161 North Port-Bradenton-Sarasota, FL 52.1                  3.3 -1.0% 60
    162 Peabody, MA  NECTA Division 51.2                  1.1 -2.9% (26)
    163 Fresno, CA 50.7                  3.8 0.9% (89)
    164 Detroit-Livonia-Dearborn, MI Metro Div 50.5                  7.4 3.2% 56
    165 Bakersfield-Delano, CA 50.2                  2.5 -7.4% (99)
    166 Anderson, IN 49.8                  0.5 0.0% 87
    167 Kingston, NY 49.0                  1.0 -6.3% (140)
    168 Buffalo-Niagara Falls, NY 48.9                  7.4 -1.8% (50)
    169 Philadelphia City, PA 48.7                11.5 -3.6% (91)
    170 Cleveland-Elyria-Mentor, OH 48.4                15.1 -0.4% (14)
    171 Hagerstown-Martinsburg, MD-WV 47.4                  2.3 0.0% 56
    172 Jacksonville, FL 47.4                  9.1 -0.4% 3
    173 Casper, WY 46.9                  0.5 -6.7% (119)
    174 Davenport-Moline-Rock Island, IA-IL 46.7                  2.5 0.0% 35
    175 Duluth, MN-WI 46.6                  1.5 4.5% 111
    176 Elkhart-Goshen, IN 46.6                  0.6 0.0% (27)
    177 Nassau-Suffolk, NY Metro Div 46.5                23.6 -2.2% (45)
    178 Muncie, IN 46.2                  0.3 0.0% 34
    179 Shreveport-Bossier City, LA 45.9                  2.4 1.4% 11
    180 Dothan, AL 45.6                  0.7 0.0% (40)
    181 Racine, WI 45.3                  0.4 0.0% (48)
    182 Memphis, TN-MS-AR 44.9                  6.0 0.6% (31)
    183 Elmira, NY 44.6                  0.4 0.0% 50
    184 Pocatello, ID 44.4                  0.4 0.0% 106
    185 Tucson, AZ 44.2                  4.3 1.6% (17)
    186 Milwaukee-Waukesha-West Allis, WI 44.1                14.5 -1.4% (15)
    187 Burlington-South Burlington, VT NECTA 44.0                  2.2 0.0% 90
    188 Framingham, MA  NECTA Division 44.0                  5.3 -3.6% (73)
    189 Kansas City, KS 43.4                15.2 3.2% (30)
    190 Edison-New Brunswick, NJ Metro Div 43.4                24.2 -2.9% (69)
    191 Canton-Massillon, OH 43.4                  1.7 0.0% (44)
    192 Waco, TX 43.3                  1.3 0.0% 71
    193 Riverside-San Bernardino-Ontario, CA 43.0                11.2 -2.0% 66
    194 Dover, DE 43.0                  0.5 0.0% 123
    195 Lexington-Fayette, KY 42.8                  5.6 -5.1% (2)
    196 Gainesville, FL 42.7                  1.5 2.3% 68
    197 Albany-Schenectady-Troy, NY 42.4                  8.3 -3.1% (30)
    198 Washington-Arlington-Alexandria, DC-VA-MD-WV Metro Div 42.3                61.4 -1.7% (28)
    199 Colorado Springs, CO 42.2                  6.9 -5.0% (86)
    200 Waterbury, CT NECTA 42.0                  0.6 0.0% 35
    201 Chattanooga, TN-GA 41.9                  2.8 -2.3% 83
    202 Birmingham-Hoover, AL 41.7                  8.8 -0.8% 1
    203 Vineland-Millville-Bridgeton, NJ 41.6                  0.8 0.0% 55
    204 Amarillo, TX 41.4                  1.4 0.0% 3
    205 Bismarck, ND 41.3                  0.9 0.0% 23
    206 Charleston, WV 40.7                  1.9 1.8% 49
    207 Harrisburg-Carlisle, PA 40.7                  4.9 1.4% 34
    208 Fayetteville-Springdale-Rogers, AR-MO 40.6                  1.8 -3.5% 11
    209 Napa, CA 40.6                  0.6 0.0% (20)
    210 Northern Virginia, VA 40.1                38.9 -1.7% (50)
    211 Palm Coast, FL 40.1                  0.9 0.0% 60
    212 Atlantic City-Hammonton, NJ 40.0                  0.8 0.0% 53
    213 Eau Claire, WI 39.8                  0.9 0.0% 0
    214 Fairbanks, AK 39.7                  0.5 0.0% (38)
    215 Nashua, NH-MA  NECTA Division 39.4                  1.9 -5.0% (162)
    216 Providence-Fall River-Warwick, RI-MA NECTA 39.2                10.0 -4.1% (32)
    217 San Diego-Carlsbad-San Marcos, CA 38.9                24.0 -1.8% (93)
    218 Bergen-Hudson-Passaic, NJ 38.7                17.3 -2.4% (38)
    219 Fort Worth-Arlington, TX Metro Div 38.6                13.2 -2.9% (40)
    220 New Bedford, MA NECTA 38.6                  0.6 0.0% 10
    221 Green Bay, WI 38.5                  1.9 -3.4% (49)
    222 Pittsfield, MA NECTA 38.5                  0.5 0.0% 28
    223 Vallejo-Fairfield, CA 38.1                  1.1 -2.9% 6
    224 Lancaster, PA 37.7                  3.1 0.0% (2)
    225 Odessa, TX 37.7                  0.5 0.0% (120)
    226 Bethesda-Rockville-Frederick, MD Metro Div 37.5                13.7 -4.8% (76)
    227 Hanford-Corcoran, CA 37.5                  0.2 0.0% (2)
    228 Calvert-Charles-Prince George’s, MD 37.4                  5.2 -5.5% (181)
    229 Lafayette, LA 37.2                  2.5 -5.1% 47
    230 Savannah, GA 37.1                  1.3 -4.8% (26)
    231 Newark-Union, NJ-PA Metro Div 36.6                18.5 -1.8% (100)
    232 Kansas City, MO 36.5                14.7 -1.6% (1)
    233 Virginia Beach-Norfolk-Newport News, VA-NC 36.4                11.2 -2.9% (47)
    234 Peoria, IL 35.2                  2.2 -8.3% (128)
    235 Lubbock, TX 35.1                  3.9 -0.8% 53
    236 Richmond, VA 35.0                  8.1 2.1% 47
    237 Putnam-Rockland-Westchester, NY 34.7                12.6 -2.1% (59)
    238 Syracuse, NY 34.4                  4.5 -3.6% (55)
    239 Tulsa, OK 33.6                  7.7 -2.5% (45)
    240 Punta Gorda, FL 33.6                  0.4 0.0% 9
    241 Oakland-Fremont-Hayward, CA Metro Div 33.4                21.4 -2.3% (41)
    242 Little Rock-North Little Rock-Conway, AR 33.3                  7.1 -2.3% 24
    243 Albuquerque, NM 32.9                  7.4 -7.9% (212)
    244 Reading, PA 32.7                  1.3 -4.9% (160)
    245 Chico, CA 32.2                  1.0 -6.3% (196)
    246 Johnstown, PA 31.7                  0.7 -4.3% (80)
    247 Tuscaloosa, AL 31.5                  0.8 0.0% (66)
    248 Beaumont-Port Arthur, TX 31.2                  1.4 -2.3% (4)
    249 Rochester, NY 30.9                  8.4 -6.7% (106)
    250 Pensacola-Ferry Pass-Brent, FL 30.8                  2.3 -2.8% 22
    251 Columbus, GA-AL 30.3                  1.5 0.0% (25)
    252 Merced, CA 30.1                  0.4 0.0% 60
    253 Poughkeepsie-Newburgh-Middletown, NY 30.0                  3.6 -2.7% (29)
    254 Salinas, CA 30.0                  1.5 -4.3% (9)
    255 Bangor, ME NECTA 29.9                  1.0 -9.1% (121)
    256 Idaho Falls, ID 29.6                  0.9 -6.9% 33
    257 Medford, OR 29.6                  1.4 -6.7% (147)
    258 Lakeland-Winter Haven, FL 29.3                  1.5 -4.2% (73)
    259 Sacramento–Arden-Arcade–Roseville, CA 28.3                14.7 -4.5% (11)
    260 Lake County-Kenosha County, IL-WI Metro Div 28.1                  3.7 -5.1% (133)
    261 Brownsville-Harlingen, TX 28.1                  1.1 3.0% 7
    262 Rapid City, SD 27.4                  0.8 -11.1% (137)
    263 Jackson, TN 27.3                  0.5 0.0% 31
    264 Owensboro, KY 26.9                  0.4 -14.3% 17
    265 Morristown, TN 26.8                  0.4 0.0% 5
    266 Norwich-New London, CT-RI NECTA 26.6                  1.3 0.0% (43)
    267 Santa Cruz-Watsonville, CA 26.5                  0.8 0.0% 0
    268 Greensboro-High Point, NC 26.2                  4.9 -7.0% (124)
    269 Roanoke, VA 25.5                  1.7 -5.5% (70)
    270 Wichita, KS 25.3                  4.3 0.0% 39
    271 Sheboygan, WI 25.2                  0.2 0.0% 20
    272 Camden, NJ Metro Div 24.8                  6.2 -9.7% 38
    273 Deltona-Daytona Beach-Ormond Beach, FL 23.8                  1.8 -6.9% (109)
    274 Stockton, CA 23.5                  1.9 -6.6% (5)
    275 Appleton, WI 23.2                  1.5 -6.3% (73)
    276 Portland-South Portland-Biddeford, ME NECTA 22.2                  3.1 -2.1% 38
    277 Greeley, CO 22.0                  0.7 -4.8% 23
    278 Johnson City, TN 21.7                  1.4 2.5% 30
    279 Niles-Benton Harbor, MI 21.5                  0.5 0.0% 17
    280 Evansville, IN-KY 21.3                  1.9 -3.4% (34)
    281 Des Moines-West Des Moines, IA 21.3                  7.0 -2.8% (65)
    282 Baltimore City, MD 20.9                  3.8 -4.2% (109)
    283 Wilmington, DE-MD-NJ Metro Div 20.5                  4.4 -4.3% (44)
    284 Dayton, OH 19.7                  8.5 -3.8% (5)
    285 Florence-Muscle Shoals, AL 19.4                  0.4 0.0% 7
    286 Anniston-Oxford, AL 18.7                  0.6 0.0% 29
    287 Panama City-Lynn Haven-Panama City Beach, FL 18.6                  1.1 -3.0% 12
    288 Salem, OR 18.3                  1.0 -6.3% (100)
    289 Decatur, IL 18.2                  0.6 -10.0% (189)
    290 Ocala, FL 18.0                  0.9 0.0% (76)
    291 Palm Bay-Melbourne-Titusville, FL 17.4                  1.9 -5.0% (93)
    292 Brockton-Bridgewater-Easton, MA  NECTA Division 17.4                  0.6 -14.3% (129)
    293 Youngstown-Warren-Boardman, OH-PA 17.3                  2.0 -3.2% 12
    294 Visalia-Porterville, CA 17.3                  0.8 -4.0% 10
    295 Oklahoma City, OK 17.1                  8.1 -2.4% (52)
    296 Reno-Sparks, NV 16.9                  1.9 -3.4% (36)
    297 Springfield, IL 15.7                  1.4 -2.3% (4)
    298 Lowell-Billerica-Chelmsford, MA-NH  NECTA Division 15.5                  3.7 -4.3% (20)
    299 Topeka, KS 15.5                  1.4 -6.7% (226)
    300 Wausau, WI 15.1                  0.4 0.0% (2)
    301 Bloomington-Normal, IL 14.6                  0.7 -12.5% (149)
    302 Kalamazoo-Portage, MI 14.4                  0.9 0.0% 0
    303 Lewiston-Auburn, ME NECTA 13.9                  0.6 -19.0% (141)
    304 Corvallis, OR 13.8                  0.6 -14.3% 7
    305 Scranton–Wilkes-Barre, PA 13.3                  3.8 -3.4% (68)
    306 Danville, IL 12.9                  0.2 0.0% (9)
    307 Crestview-Fort Walton Beach-Destin, FL 12.5                  0.9 -6.7% (20)
    308 Modesto, CA 12.1                  0.9 0.0% 5
    309 Leominster-Fitchburg-Gardner, MA NECTA 11.9                  0.4 -7.7% (250)
    310 Erie, PA 10.5                  1.3 -7.1% (128)
    311 Midland, TX 10.3                  0.9 -15.6% (29)
    312 Lake Havasu City-Kingman, AZ 9.9                  0.6 -10.0% (38)
    313 San Angelo, TX 9.7                  0.9 -10.0% (59)
    314 New Haven, CT NECTA 9.5                  4.1 -4.7% (29)
    315 Rockford, IL 8.3                  1.3 -13.3% (64)
    316 Utica-Rome, NY 7.8                  1.5 -10.0% (36)
    317 Jackson, MI 4.7                  0.3 -10.0% (16)

  • Small Cities Information Jobs – 2014 Best Cities Rankings

    View the Best Cities for Information Jobs 2014 List

    2014 MSA Info Overall Ranking Area Weighted INDEX 2013 Information Employment 20012-13 Info Growth 2014 Ranking Change from 2013 – Small MSAs
    1 Janesville, WI 97.9                  1.5 18.4% 51
    2 Flint, MI 97.3                  4.2 9.5% 0
    3 Logan, UT-ID 93.3                  0.9 12.5% 6
    4 Abilene, TX 88.2                  1.2 9.1% 34
    5 Laredo, TX 88.1                  0.7 16.7% 11
    6 San Luis Obispo-Paso Robles, CA 87.3                  1.4 7.7% 12
    7 Rochester, MN 87.2                  1.7 6.2% 0
    8 Fond du Lac, WI 86.5                  0.9 12.5% 79
    9 College Station-Bryan, TX 84.5                  1.3 0.0% (6)
    10 Portsmouth, NH-ME NECTA 84.0                  2.0 1.7% 4
    11 Lafayette, IN 80.5                  1.1 6.5% 19
    12 Tyler, TX 80.3                  2.3 2.9% (8)
    13 Champaign-Urbana, IL 80.1                  2.5 10.4% 104
    14 Hickory-Lenoir-Morganton, NC 75.6                  1.0 0.0% (4)
    15 Cheyenne, WY 75.1                  1.1 0.0% (14)
    16 Binghamton, NY 74.6                  1.9 11.8% 35
    17 Sebastian-Vero Beach, FL 73.9                  0.7 0.0% 2
    18 Oshkosh-Neenah, WI 72.9                  1.6 2.1% 15
    19 Greenville, NC 72.6                  1.0 11.1% 24
    20 Bend, OR 72.4                  1.4 0.0% 63
    21 Saginaw-Saginaw Township North, MI 72.1                  1.4 7.7% 85
    22 Las Cruces, NM 71.9                  0.9 0.0% (5)
    23 Auburn-Opelika, AL 71.7                  0.5 0.0% 91
    24 Flagstaff, AZ 71.6                  0.4 0.0% 4
    25 Lewiston, ID-WA 70.8                  0.4 0.0% 1
    26 Cleveland, TN 70.1                  0.3 0.0% (3)
    27 Bay City, MI 70.1                  0.5 25.0% 53
    28 Eugene-Springfield, OR 69.7                  3.3 0.0% 22
    29 Kingsport-Bristol-Bristol, TN-VA 68.7                  2.1 0.0% 121
    30 Muskegon-Norton Shores, MI 68.2                  0.8 14.3% 97
    31 Clarksville, TN-KY 67.7                  1.1 -3.0% (20)
    32 Columbus, IN 67.6                  0.5 0.0% (24)
    33 Wilmington, NC 66.8                  2.9 2.4% 46
    34 Fargo, ND-MN 66.2                  3.3 3.1% 44
    35 Prescott, AZ 65.9                  0.6 0.0% 0
    36 Burlington, NC 65.7                  0.5 0.0% 41
    37 Sherman-Denison, TX 65.2                  0.5 0.0% 54
    38 Bloomington, IN 65.0                  1.3 0.0% 1
    39 Rochester-Dover, NH-ME NECTA 64.8                  1.2 0.0% (27)
    40 St. Cloud, MN 64.8                  1.7 0.0% (4)
    41 Glens Falls, NY 64.5                  1.0 3.4% (4)
    42 Madera-Chowchilla, CA 63.7                  0.4 20.0% 17
    43 Haverhill-North Andover-Amesbury, MA-NH NECTA Div 63.7                  0.9 -3.7% 14
    44 Pueblo, CO 63.4                  0.7 5.0% 21
    45 Yuma, AZ 62.4                  0.5 -16.7% (39)
    46 Sioux Falls, SD 62.2                  2.7 1.3% 40
    47 Kokomo, IN 61.9                  0.4 0.0% (22)
    48 Naples-Marco Island, FL 61.7                  1.5 0.0% (6)
    49 Victoria, TX 61.6                  0.5 0.0% 76
    50 Decatur, AL 61.3                  0.3 0.0% 16
    51 Ithaca, NY 61.3                  0.5 0.0% (2)
    52 Altoona, PA 61.2                  0.9 4.0% 30
    53 St. George, UT 60.6                  0.7 0.0% (38)
    54 Barnstable Town, MA NECTA 60.4                  1.6 0.0% (23)
    55 Gadsden, AL 60.1                  0.4 22.2% 98
    56 Fort Collins-Loveland, CO 59.2                  2.4 0.0% (15)
    57 Manchester, NH NECTA 59.1                  3.1 -3.1% (25)
    58 Santa Fe, NM 58.8                  0.9 13.0% 94
    59 Killeen-Temple-Fort Hood, TX 58.6                  2.2 1.5% 1
    60 Grand Junction, CO 58.6                  0.8 0.0% 42
    61 Longview, TX 58.6                  1.4 0.0% (13)
    62 Yuba City, CA 58.5                  0.4 0.0% 0
    63 Fort Smith, AR-OK 58.1                  1.3 -4.9% (58)
    64 Lawton, OK 58.1                  0.5 0.0% 46
    65 Redding, CA 58.0                  0.6 5.6% 6
    66 Terre Haute, IN 57.7                  0.7 0.0% (21)
    67 South Bend-Mishawaka, IN-MI 57.2                  1.8 0.0% 18
    68 La Crosse, WI-MN 57.2                  1.1 0.0% (28)
    69 Cedar Rapids, IA 56.9                  4.9 -0.7% (15)
    70 Fayetteville, NC 56.6                  1.5 0.0% 22
    71 Texarkana, TX-Texarkana, AR 56.3                  0.5 0.0% (1)
    72 Grand Forks, ND-MN 55.3                  0.6 0.0% 31
    73 Kankakee-Bradley, IL 54.5                  0.5 0.0% 86
    74 Port St. Lucie, FL 54.3                  1.4 5.1% 42
    75 Holland-Grand Haven, MI 53.9                  0.7 0.0% (46)
    76 Wichita Falls, TX 53.7                  1.1 10.0% 28
    77 El Centro, CA 53.7                  0.4 0.0% (50)
    78 Coeur d’Alene, ID 53.0                  0.7 16.7% 64
    79 Peabody, MA  NECTA Division 51.2                  1.1 -2.9% (21)
    80 Anderson, IN 49.8                  0.5 0.0% 31
    81 Kingston, NY 49.0                  1.0 -6.3% (68)
    82 Hagerstown-Martinsburg, MD-WV 47.4                  2.3 0.0% 14
    83 Casper, WY 46.9                  0.5 -6.7% (61)
    84 Duluth, MN-WI 46.6                  1.5 4.5% 49
    85 Elkhart-Goshen, IN 46.6                  0.6 0.0% (22)
    86 Muncie, IN 46.2                  0.3 0.0% 2
    87 Dothan, AL 45.6                  0.7 0.0% (26)
    88 Racine, WI 45.3                  0.4 0.0% (33)
    89 Elmira, NY 44.6                  0.4 0.0% 11
    90 Pocatello, ID 44.4                  0.4 0.0% 47
    91 Burlington-South Burlington, VT NECTA 44.0                  2.2 0.0% 37
    92 Waco, TX 43.3                  1.3 0.0% 26
    93 Dover, DE 43.0                  0.5 0.0% 67
    94 Gainesville, FL 42.7                  1.5 2.3% 25
    95 Waterbury, CT NECTA 42.0                  0.6 0.0% 6
    96 Vineland-Millville-Bridgeton, NJ 41.6                  0.8 0.0% 19
    97 Amarillo, TX 41.4                  1.4 0.0% (13)
    98 Bismarck, ND 41.3                  0.9 0.0% (1)
    99 Charleston, WV 40.7                  1.9 1.8% 14
    100 Napa, CA 40.6                  0.6 0.0% (24)
    101 Palm Coast, FL 40.1                  0.9 0.0% 23
    102 Atlantic City-Hammonton, NJ 40.0                  0.8 0.0% 18
    103 Eau Claire, WI 39.8                  0.9 0.0% (14)
    104 Fairbanks, AK 39.7                  0.5 0.0% (32)
    105 Nashua, NH-MA  NECTA Division 39.4                  1.9 -5.0% (84)
    106 New Bedford, MA NECTA 38.6                  0.6 0.0% (7)
    107 Pittsfield, MA NECTA 38.5                  0.5 0.0% 1
    108 Vallejo-Fairfield, CA 38.1                  1.1 -2.9% (10)
    109 Odessa, TX 37.7                  0.5 0.0% (63)
    110 Hanford-Corcoran, CA 37.5                  0.2 0.0% (16)
    111 Lubbock, TX 35.1                  3.9 -0.8% 24
    112 Punta Gorda, FL 33.6                  0.4 0.0% (5)
    113 Chico, CA 32.2                  1.0 -6.3% (93)
    114 Johnstown, PA 31.7                  0.7 -4.3% (45)
    115 Tuscaloosa, AL 31.5                  0.8 0.0% (42)
    116 Columbus, GA-AL 30.3                  1.5 0.0% (21)
    117 Merced, CA 30.1                  0.4 0.0% 39
    118 Salinas, CA 30.0                  1.5 -4.3% (13)
    119 Bangor, ME NECTA 29.9                  1.0 -9.1% (63)
    120 Idaho Falls, ID 29.6                  0.9 -6.9% 16
    121 Medford, OR 29.6                  1.4 -6.7% (74)
    122 Brownsville-Harlingen, TX 28.1                  1.1 3.0% 0
    123 Rapid City, SD 27.4                  0.8 -11.1% (70)
    124 Jackson, TN 27.3                  0.5 0.0% 17
    125 Owensboro, KY 26.9                  0.4 -14.3% 6
    126 Morristown, TN 26.8                  0.4 0.0% (3)
    127 Norwich-New London, CT-RI NECTA 26.6                  1.3 0.0% (34)
    128 Santa Cruz-Watsonville, CA 26.5                  0.8 0.0% (7)
    129 Sheboygan, WI 25.2                  0.2 0.0% 9
    130 Appleton, WI 23.2                  1.5 -6.3% (49)
    131 Greeley, CO 22.0                  0.7 -4.8% 16
    132 Johnson City, TN 21.7                  1.4 2.5% 22
    133 Niles-Benton Harbor, MI 21.5                  0.5 0.0% 10
    134 Florence-Muscle Shoals, AL 19.4                  0.4 0.0% 5
    135 Anniston-Oxford, AL 18.7                  0.6 0.0% 23
    136 Panama City-Lynn Haven-Panama City Beach, FL 18.6                  1.1 -3.0% 10
    137 Salem, OR 18.3                  1.0 -6.3% (62)
    138 Decatur, IL 18.2                  0.6 -10.0% (94)
    139 Ocala, FL 18.0                  0.9 0.0% (49)
    140 Brockton-Bridgewater-Easton, MA  NECTA Division 17.4                  0.6 -14.3% (72)
    141 Visalia-Porterville, CA 17.3                  0.8 -4.0% 10
    142 Springfield, IL 15.7                  1.4 -2.3% (2)
    143 Lowell-Billerica-Chelmsford, MA-NH  NECTA Division 15.5                  3.7 -4.3% (14)
    144 Topeka, KS 15.5                  1.4 -6.7% (110)
    145 Wausau, WI 15.1                  0.4 0.0% 0
    146 Bloomington-Normal, IL 14.6                  0.7 -12.5% (82)
    147 Kalamazoo-Portage, MI 14.4                  0.9 0.0% 2
    148 Lewiston-Auburn, ME NECTA 13.9                  0.6 -19.0% (81)
    149 Corvallis, OR 13.8                  0.6 -14.3% 6
    150 Danville, IL 12.9                  0.2 0.0% (6)
    151 Crestview-Fort Walton Beach-Destin, FL 12.5                  0.9 -6.7% (17)
    152 Leominster-Fitchburg-Gardner, MA NECTA 11.9                  0.4 -7.7% (128)
    153 Erie, PA 10.5                  1.3 -7.1% (79)
    154 Midland, TX 10.3                  0.9 -15.6% (22)
    155 Lake Havasu City-Kingman, AZ 9.9                  0.6 -10.0% (29)
    156 San Angelo, TX 9.7                  0.9 -10.0% (44)
    158 Rockford, IL 8.3                  1.3 -13.3% (49)
    159 Utica-Rome, NY 7.8                  1.5 -10.0% (29)
    160 Jackson, MI 4.7                  0.3 -10.0% (12)

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